Abstract

A method includes a computing device verifying authenticity of a blockchain-encoded record representing a statement of words and an entigen group to produce an authenticity indicator where a set of identigens is determined utilizing a knowledge database for each word to produce sets of identigens and where the sets of identigens is interpreted to produce the entigen group. When the authenticity indicator indicates an authentic status, the method further includes interpreting, based on an updated knowledge database, updated sets of identigens to produce an updated entigen group. The method further includes updating the blockchain-encoded record to represent the statement and the updated entigen group to facilitate subsequent utilization of an updated validated interpretation of the statement as the updated entigen group.

IPC Classes  ?

• H04L 9/32 - Arrangements for secret or secure communicationsNetwork security protocols including means for verifying the identity or authority of a user of the system
• H04L 9/00 - Arrangements for secret or secure communicationsNetwork security protocols
• H04L 9/06 - Arrangements for secret or secure communicationsNetwork security protocols the encryption apparatus using shift registers or memories for blockwise coding, e.g. D.E.S. systems
• H04L 9/08 - Key distribution

Abstract

A method executed by a computing device includes determining a set of identigens for each query word of a query to produce sets of identigens, where a set of identigens represents different meanings of a word of the query. The method further includes interpreting the sets of identigens to produce a query entigen group. The method further includes accessing a knowledge database utilizing the query entigen group to recover a preliminary response entigen group. The method further includes modifying an answer breadth level based on the preliminary response entigen group to produce an updated answer breadth level. The method further includes accessing the knowledge database utilizing the query entigen group to recover a secondary response entigen group the updated answer breadth level.

IPC Classes  ?

• G06F 40/289 - Phrasal analysis, e.g. finite state techniques or chunking
• G06F 40/247 - ThesaurusesSynonyms
• G06F 40/284 - Lexical analysis, e.g. tokenisation or collocates
• G06F 40/30 - Semantic analysis
• G06N 5/022 - Knowledge engineeringKnowledge acquisition
• G06N 5/025 - Extracting rules from data
• G06N 5/04 - Inference or reasoning models

Abstract

A method for execution by a computing device includes identifying sets of identigens for words of a phrase. The method further includes identifying levels of pairing of sequentially adjacent identigens between each adjacent set of identigens and interpreting every permutation of sequentially adjacent identigens to produce permutations of entigen groups. The method further includes determining permutation scores for the permutations of entigen groups and selecting an entigen group based on the permutation scores to produce a selected entigen group that represents a most likely meaning interpretation of the phrase.

IPC Classes  ?

• G06F 40/284 - Lexical analysis, e.g. tokenisation or collocates
• G06F 16/903 - Querying
• G06F 16/9032 - Query formulation
• G06F 40/253 - Grammatical analysisStyle critique

Abstract

A method performed by a computing device includes obtaining impaired content for a topic that includes a series of words, and determining a set of identigens for each word of the series of words to produce sets of identigens. The method further includes interpreting, using identigen pairing rules of a knowledge database, the sets of identigens to determine a most likely meaning interpretation of the impaired content and produce an interim entigen group. The method further includes recovering an improved entigen group for the topic from the knowledge database utilizing the interim entigen group and based on a knowledge defect of the interim entigen group caused by an impairment of the impaired content.

IPC Classes  ?

• G06F 16/215 - Improving data qualityData cleansing, e.g. de-duplication, removing invalid entries or correcting typographical errors
• G06F 16/28 - Databases characterised by their database models, e.g. relational or object models
• G06F 16/3329 - Natural language query formulation
• G06F 16/3332 - Query translation
• G06F 16/334 - Query execution
• G06F 40/242 - Dictionaries
• G06F 40/247 - ThesaurusesSynonyms
• G06F 40/30 - Semantic analysis

Abstract

A method executed by a computing device includes determining a set of identigens for each word of a query to produce sets of identigens, where a set of identigens represents different meanings of a word of the query. The method further includes interpreting, using identigen pairing rules, the sets of identigens to produce a query entigen group that represents a most likely meaning interpretation of the query. The method further includes identifying common associated entigens of a knowledge database utilizing the query entigen group. The method further includes selecting a first common associated entigen of the common associated entigens utilizing the query entigen group and generating a response entigen group based on the first common associated entigen and the query entigen group. The method further includes generating a response to the query utilizing the response entigen group, where the response includes at least one response word.

IPC Classes  ?

• G06F 40/289 - Phrasal analysis, e.g. finite state techniques or chunking
• G06F 40/247 - ThesaurusesSynonyms
• G06F 40/284 - Lexical analysis, e.g. tokenisation or collocates
• G06N 5/022 - Knowledge engineeringKnowledge acquisition
• G06N 5/04 - Inference or reasoning models

Abstract

A neuro-symbolic retrieval augmented generation hybrid method includes determining a set of identigens for each word of a query to produce a plurality of sets of identigens. The method further includes interpreting, based on a first knowledge database, the plurality of sets of identigens to produce a first entigen group and generating a first preliminary query response based on the first entigen group. The method further includes interpreting, based on a second knowledge database, the plurality of sets of identigens to produce a second entigen group and generating a second preliminary query response based on the second entigen group. The method further includes comparing the first and second preliminary query responses and when the first preliminary query response and the second preliminary query response are divergent, resolving inconsistencies between the first and second preliminary query responses to produce a final query response.

IPC Classes  ?

• G06F 16/334 - Query execution
• G06F 16/332 - Query formulation
• G06F 16/3332 - Query translation
• G06F 16/338 - Presentation of query results
• G06F 16/353 - ClusteringClassification into predefined classes
• G06F 40/30 - Semantic analysis
• G06N 5/04 - Inference or reasoning models

Abstract

A neuro-symbolic retrieval augmented generation hybrid method includes determining a set of identigens for each word of patent claim elements to produce sets of identigens and interpreting pairs of adjacent identigens of adjacent sets of identigens to determine a most likely meaning of the claim elements and produce a claim entigen group. The method further includes determining a level of match between the claim entigen group and a comparison matter entigen group. When the level of match between the claim entigen group and the comparison matter entigen group is greater than a threshold level, the method further includes indicating potential utilization of the claim by the comparison matter or potential prior art status of the comparison matter.

IPC Classes  ?

• G06F 40/237 - Lexical tools
• G06F 16/334 - Query execution
• G06F 16/35 - ClusteringClassification
• G06F 40/30 - Semantic analysis
• G06N 5/022 - Knowledge engineeringKnowledge acquisition

Abstract

A neuro-symbolic retrieval augmented generation hybrid method includes detecting an incomplete entigen group within a knowledge database. The incomplete entigen group includes entigens and one or more entigen relationships between at least some of the entigens. The incomplete entigen group represents knowledge of a topic. The method further includes obtaining additive content for the topic based on the incomplete entigen group and generating an additive entigen group based on the additive content. The method further includes updating the incomplete entigen group utilizing the additive entigen group to produce an updated entigen group. The method further includes indicating that the updated entigen group has an un-curated status when the additive entigen group conflicts with the incomplete entigen group.

IPC Classes  ?

• G06F 40/30 - Semantic analysis

Abstract

A method executed by a computing device includes determining a set of identigens for each widely-known word of a query to produce sets of identigens. A set of identigens of the sets of identigens represents one or more different meanings of a word of the query. The method further includes determining another set of identigens for a remaining word to produce an alternate set of identigens. The method further includes selecting an identigen for each set of identigens to produce a query entigen group. The method further includes matching the query entigen group to a set of response entigens to produce a response entigen group as a query response.

IPC Classes  ?

• G06F 40/289 - Phrasal analysis, e.g. finite state techniques or chunking
• G06F 16/334 - Query execution
• G06F 16/36 - Creation of semantic tools, e.g. ontology or thesauri
• G06F 40/237 - Lexical tools
• G06F 40/247 - ThesaurusesSynonyms
• G06F 40/30 - Semantic analysis

Abstract

A method performed by a computing device includes generating a neural network representation of a subjective query and generating a query entigen group as a symbolic architecture representation of the subjective query. The method further includes identifying one or more characteristic entigen categories for a subjective category entigen of the query entigen group. The method further includes generating a symbolic architecture representation of a query response for the subjective query that includes a set of response entigens based on the one or more characteristic entigen categories. The set of response entigens provides an answer for the subjective query.

IPC Classes  ?

• G06F 16/33 - Querying
• G06F 16/338 - Presentation of query results
• G06F 40/279 - Recognition of textual entities

Abstract

A method executed by a computing device includes determining that a set of words are included in a word set. The method further includes determining a set of identigens for each word of the word set to produce sets of identigens, where a set of identigens of the sets of identigens represents one or more different meanings of a word of the word set. The method further includes interpreting, using identigen pairing rules, the sets of identigens to produce an entigen set. The method further includes assigning a single new entigen to represent the entigen set, where the single new entigen represents a most likely meaning interpretation of the word set.

IPC Classes  ?

• G06F 16/23 - Updating
• G06F 16/2452 - Query translation
• G06F 16/2457 - Query processing with adaptation to user needs
• G06F 16/248 - Presentation of query results

Abstract

A method executed by a computing device includes determining to extend knowledge within a knowledge database for an object represented by linked entigens of an entigen group based on a deficiency of the entigen group. The method further includes determining a set of identigens for each word of a phrase associated with the object to produce sets of identigens. The method further includes interpreting the sets of identigens to determine a most likely meaning interpretation of the phrase and produce a new entigen group. The method further includes updating the entigen group utilizing the new entigen group to produce a curated entigen group such that a deficiency of the entigen group is resolved providing more accurate and more complete knowledge of the object.

IPC Classes  ?

• G06N 5/02 - Knowledge representationSymbolic representation
• G06F 16/36 - Creation of semantic tools, e.g. ontology or thesauri
• G06F 40/30 - Semantic analysis

Abstract

A method includes generating a content entigen group for content using identigen pairing rules. The method further includes obtaining a contradicting entigen group based on the content entigen group. The method further includes updating the knowledge database to include the content entigen group. A contradicted entigen of the content entigen group is established to indicate duplication of a contradicted entigen of the contradicting entigen group.

IPC Classes  ?

• G06N 5/022 - Knowledge engineeringKnowledge acquisition
• G06N 5/04 - Inference or reasoning models

Abstract

A method includes selecting an entigen group from a knowledge database. The entigen group is a most likely meaning of a phrase of a string of words. An entigen of the entigen group corresponds to a selected identigen from a set of identigens regarding a word of the string of words. The set of identigens represent different meanings of the word. The method further includes identifying other entigen groups of alternate phrases having a similar most likely meaning from the knowledge database. The alternate phrases are different permutations of the string of words. The method further includes determining a dominant sentiment the other entigen groups and generating an updated clarifying entigen group based on the sentiment.

IPC Classes  ?

• G06F 16/33 - Querying
• G06F 16/332 - Query formulation
• G06F 16/338 - Presentation of query results
• G06F 16/35 - ClusteringClassification
• G06F 40/30 - Semantic analysis
• G06N 5/04 - Inference or reasoning models

Abstract

A method executed by a computing device includes determining a set of identigens for each query word of a query to produce sets of identigens. A set of identigens of the sets of identigens represents one or more different meanings of a query word of the query. The method further includes determining that a first query word is associated with a first query command. When selecting the first query command, the method further includes interpreting remaining sets of identigens to produce a query entigen group that represents a most likely meaning interpretation of remaining query words. The method further includes accessing a knowledge database utilizing the query entigen group to obtain entigen information and outputting a response based on the entigen information and the first query command.

IPC Classes  ?

• G06F 16/33 - Querying
• G06F 40/30 - Semantic analysis
• G06N 5/02 - Knowledge representationSymbolic representation

Abstract

A method includes identifying identigens for each word of a phrase, where the identigens of a first word of the phrase includes one or more different meanings of the first word. The method further includes identifying two adjacent words of the phrase that are lacking an identigen pairing rule and determining whether the identigen pairing rule can be inferred for the two adjacent words based on known identigen pairings of other words of the trusted phrase. When the identigen pairing rule can be inferred for the two adjacent words, the method further includes adding to a knowledge database the identigen pairing rule of the two adjacent words.

IPC Classes  ?

• G06F 40/284 - Lexical analysis, e.g. tokenisation or collocates
• G06F 16/903 - Querying
• G06F 16/906 - ClusteringClassification
• G06F 40/205 - Parsing
• G06N 5/04 - Inference or reasoning models

Abstract

A method for execution by a computing device includes obtaining a set of media element identigens for media elements of media to produce sets of media element identigens. The sets of media element identigens are possible interpretations of a media element. The method further includes generating a set of relationships between media elements. The relationships provide a list of one or more ways in which the media elements are related. The method further includes processing different permutations of the sets of media element identigens using the set of relationships to generate textual descriptions as a proxy for an entigen group. The entigen group represents a most likely interpretation of the media.

IPC Classes  ?

• G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
• A01G 3/00 - Cutting implements specially adapted for horticultural purposesDelimbing standing trees
• A01G 5/00 - Floral handling
• A23N 15/00 - Machines or apparatus for other treatment of fruits or vegetables for human purposesMachines or apparatus for topping or skinning flower bulbs
• G06T 7/11 - Region-based segmentation
• G06T 7/70 - Determining position or orientation of objects or cameras

Abstract

A method executed by a computing device includes determining a set of identigens for a phrase to produce sets of identigens. A set of identigens of the sets of identigens represents one or more different meanings of a word of the phrase. The method further includes interpreting, based on identigen pairing rules of a knowledge database, pairs of sequentially adjacent identigens of adjacent sets of identigens of the sets of identigens to determine a first most likely meaning interpretation of the phrase and produce a first phrase entigen group of phrase entigen groups. The method further includes identifying an inconsistency between at least two phrase entigen groups of the phrase entigen groups and obtaining an inconsistency clarification based on the inconsistency. The method further includes selecting one phrase entigen group of the phrase entigen groups based on the inconsistency clarification to produce a final phrase entigen group.

IPC Classes  ?

• G06F 16/242 - Query formulation
• G06F 16/2455 - Query execution
• G06F 16/28 - Databases characterised by their database models, e.g. relational or object models
• G06F 40/289 - Phrasal analysis, e.g. finite state techniques or chunking

Abstract

A method executed by a computing device includes determining a set of identigens for each query word of a query to produce sets of identigens, where a set of identigens represents different meanings of a word of the query. The method further includes interpreting the sets of identigens to produce a query entigen group. The method further includes accessing a knowledge database utilizing the query entigen group to recover a preliminary response entigen group. The method further includes modifying an answer breadth level based on a response to the preliminary response entigen group to produce an updated answer breadth level. The method further includes accessing the knowledge database utilizing the query entigen group to recover a secondary response entigen group the updated answer breadth level.

IPC Classes  ?

• G06F 40/289 - Phrasal analysis, e.g. finite state techniques or chunking
• G06F 40/247 - ThesaurusesSynonyms
• G06F 40/284 - Lexical analysis, e.g. tokenisation or collocates
• G06F 40/30 - Semantic analysis
• G06N 5/022 - Knowledge engineeringKnowledge acquisition
• G06N 5/025 - Extracting rules from data
• G06N 5/04 - Inference or reasoning models

Abstract

A method performed by a computing device includes generating a comparative query entigen group set based on a comparative query in accordance with identigen rules, where the comparative query entigen group set represents a most likely interpretation of the comparative query. The method further includes obtaining a first response entigen group from a knowledge database based on a first comparative query entigen group of the comparative query entigen group set. The method further includes obtaining a second response entigen group from the knowledge database based on a second comparative query entigen group of the comparative query entigen group set. The method further includes generating a comparative response based on the first response entigen group and the second response entigen group.

IPC Classes  ?

• G06N 5/025 - Extracting rules from data
• G06F 16/245 - Query processing
• G06F 16/2455 - Query execution
• G06F 16/2457 - Query processing with adaptation to user needs
• G06F 16/903 - Querying

Abstract

A method for execution by a computing device includes identifying sets of identigens for words of a phrase. The method further includes selecting, based on identigen pairing rules of a knowledge database, a first identigen of a first set of identigens for a first word that pairs with at least one corresponding sequentially adjacent identigen of a second set of identigens. The method further includes selecting the first identigen of the first set of identigens as a subsequent identigen corresponding to a subsequent occurrence of the first word within the sequence of words. The method further includes interpreting, in accordance with the identigen pairing rules and based on the first identigen selection for the subsequent occurrence of the first word, the sets of identigens to produce an entigen group that represents a most likely meaning interpretation of the phrase.

IPC Classes  ?

• G06F 40/284 - Lexical analysis, e.g. tokenisation or collocates
• G06F 16/903 - Querying
• G06F 16/9032 - Query formulation
• G06F 40/253 - Grammatical analysisStyle critique

Abstract

A method executed by a computing device includes determining a set of identigens for each phrase word of a phrase to produce sets of identigens. A set of identigens of the sets of identigens represents one or more different meanings of a phrase word of the phrase. The method further includes obtaining sensor information for one or more phrase words of the phrase. The method further includes selecting an identigen of a first set of identigens based on the sensor information to produce a first identigen selection for the first set of identigens having a selected meaning of one or more different meanings of the first phrase word. The method further includes interpreting remaining sets of identigens of the sets of identigens to produce an entigen group so that the entigen group represents a most likely meaning interpretation of the phrase.

IPC Classes  ?

• G06F 40/289 - Phrasal analysis, e.g. finite state techniques or chunking
• G06F 16/33 - Querying
• G06F 16/36 - Creation of semantic tools, e.g. ontology or thesauri
• G06F 40/237 - Lexical tools
• G06F 40/247 - ThesaurusesSynonyms
• G06F 40/30 - Semantic analysis

Abstract

A method includes a computing device verifying authenticity of a blockchain-encoded record representing a statement of words and an entigen group to produce an authenticity indicator where a set of identigens is determined utilizing a knowledge database for each word to produce sets of identigens and where the sets of identigens is interpreted to produce the entigen group. When the authenticity indicator indicates an authentic status, the method further includes interpreting, based on an updated knowledge database, updated sets of identigens to produce an updated entigen group. The method further includes updating the blockchain-encoded record to represent the statement and the updated entigen group to facilitate subsequent utilization of an updated validated interpretation of the statement as the updated entigen group.

IPC Classes  ?

• H04L 9/32 - Arrangements for secret or secure communicationsNetwork security protocols including means for verifying the identity or authority of a user of the system
• H04L 9/00 - Arrangements for secret or secure communicationsNetwork security protocols
• H04L 9/06 - Arrangements for secret or secure communicationsNetwork security protocols the encryption apparatus using shift registers or memories for blockwise coding, e.g. D.E.S. systems
• H04L 9/08 - Key distribution

Abstract

A computer-implemented method includes determining a set of identigens for each word of patent claim elements to produce sets of identigens and interpreting pairs of adjacent identigens of adjacent sets of identigens to determine a most likely meaning of the claim elements and produce a claim entigen group. The method further includes determining a level of match between the claim entigen group and a comparison matter entigen group. When the level of match between the claim entigen group and the comparison matter entigen group is greater than a threshold level, the method further includes indicating potential utilization of the claim by the comparison matter or potential prior art status of the comparison matter.

IPC Classes  ?

• G06F 17/00 - Digital computing or data processing equipment or methods, specially adapted for specific functions
• G06F 16/35 - ClusteringClassification
• G06F 40/237 - Lexical tools
• G06F 40/30 - Semantic analysis
• G06N 5/022 - Knowledge engineeringKnowledge acquisition

Abstract

A method executed by a computing device includes determining a set of identigens for each word of a sequence of words to produce sets of identigens. The method further includes generating a set of identigen permutations based on the sets of identigens to produce interim knowledge representing the sequence of words. The method further includes updating the set of identigen permutations based on clarifying sets of identigens to produce an updated set of identigen permutations as updated interim knowledge. When the updated interim knowledge contains a single identigen permutation of the updated set of identigen permutations, the method further includes establishing the single identigen permutation as curated knowledge representing the sequence of words.

IPC Classes  ?

• G06F 16/31 - IndexingData structures thereforStorage structures

Abstract

A method executed by a computing device includes determining a set of identigens for each query word of a query to produce a plurality of sets of identigens. The method further includes interpreting, based on identigen pairing rules of a knowledge database, pairs of sequentially adjacent identigens of adjacent sets of identigens of the plurality of sets of identigens to determine a most likely meaning interpretation of the query and produce a query entigen group. The method further includes identifying a set of entigen variations associated with the query entigen group utilizing the knowledge database to produce an expanded query entigen group. The method further includes obtaining knowledge associated with the first entigen variation of the set of entigen variations.

IPC Classes  ?

• G06N 5/022 - Knowledge engineeringKnowledge acquisition
• G06F 16/3329 - Natural language query formulation
• G06F 16/334 - Query execution
• G06F 40/242 - Dictionaries
• G06F 40/247 - ThesaurusesSynonyms
• G06F 40/30 - Semantic analysis
• G06N 5/02 - Knowledge representationSymbolic representation
• G06N 5/025 - Extracting rules from data
• G06N 5/04 - Inference or reasoning models

Abstract

A method executed by a computing device includes determining whether a set of words are included in a word set. When the set of words are in the word set, the method further includes determining a set of identigens for each word of the word set to produce sets of identigens, where a set of identigens of the sets of identigens represents one or more different meanings of a word of the word set. The method further includes interpreting, using identigen pairing rules, the sets of identigens to produce an entigen set. The method further includes assigning a single new entigen to represent the entigen set, where the single new entigen represents a most likely meaning interpretation of the word set.

IPC Classes  ?

• G06F 17/00 - Digital computing or data processing equipment or methods, specially adapted for specific functions
• G06F 16/23 - Updating
• G06F 16/2452 - Query translation
• G06F 16/2457 - Query processing with adaptation to user needs
• G06F 16/248 - Presentation of query results

Abstract

A method performed by a computing device includes generating a comparative query entigen group set based on a comparative query in accordance with identigen rules, where the comparative query entigen group set represents a most likely interpretation of the comparative query. The method further includes obtaining a first response entigen group from a knowledge database based on a first comparative query entigen group of the comparative query entigen group set, where the first response entigen group substantially includes the first comparative query entigen group. The method further includes obtaining a second response entigen group from the knowledge database based on a second comparative query entigen group of the comparative query entigen group set, where the second response entigen group substantially includes the second comparative query entigen group. The method further includes generating a comparative response based on the first response entigen group and the second response entigen group.

IPC Classes  ?

• G06F 17/30 - Information retrieval; Database structures therefor
• G06F 16/245 - Query processing
• G06F 16/2455 - Query execution
• G06F 16/2457 - Query processing with adaptation to user needs
• G06F 16/903 - Querying
• G06N 5/025 - Extracting rules from data

Abstract

A method for execution by a computing device includes obtaining a phrase that includes string of words and generating a valid sequence of words utilizing the phrase. The method further includes identifying a set of identigens for each word of the valid sequence of words to produce sets of identigens. The method further includes identifying, for each identigen of the sets of identigens, a word type associated with phrase structure grammar rules to produce sets of identigen-type associations. The method further includes interpreting, utilizing the phrase structure grammar rules, the sets of identigen-type associations to produce an entigen group. The entigen group represents a most likely interpretation of the phrase.

IPC Classes  ?

• G06F 40/284 - Lexical analysis, e.g. tokenisation or collocates
• G06F 16/9032 - Query formulation
• G06F 16/903 - Querying
• G06F 40/253 - Grammatical analysisStyle critique

Abstract

A method performed by a computing device includes determining a set of identigens for each word of a query of a topic to produce sets of identigens. Each set of identigens represents one or more different meanings of a word of the query. The method further includes interpreting, using identigen pairing rules, the sets of identigens to determine a most likely meaning interpretation of the query and produce an excluding query entigen group with an excluding entigen. The method further includes recovering a response entigen group for the query from a knowledge database utilizing the excluding query entigen group. The response entigen group provides a response to the query.

IPC Classes  ?

• G06V 10/00 - Arrangements for image or video recognition or understanding
• G06F 16/332 - Query formulation
• G06F 40/247 - ThesaurusesSynonyms
• G06N 5/04 - Inference or reasoning models

Abstract

A method performed by a computing device includes determining a set of identigens for each word of words of a product-service query to produce sets of identigens. The method further includes interpreting, using identigen pairing rules of a knowledge database, the sets of identigens to determine a most likely meaning interpretation of the product-service query and produce a query entigen group that includes query entigens. The method further includes identifying one or more characteristic entigen categories for a subjective category entigen of the query entigen group. The method further includes recovering a set of response entigens for the product-service query from the knowledge database utilizing the query entigen group and based on the one or more characteristic entigen categories. The set of response entigens provides an answer for the product-service query.

IPC Classes  ?

• G06F 16/3332 - Query translation
• G06F 40/30 - Semantic analysis

Abstract

A method includes generating a content entigen group for content using identigen pairing rules. The method further includes obtaining a contradicting entigen group from a knowledge database based on the content entigen group. The method further includes updating the knowledge database to include the content entigen group. A contradicted entigen of the content entigen group is established to indicate duplication of a contradicted entigen of the contradicting entigen group.

IPC Classes  ?

• G06N 5/022 - Knowledge engineeringKnowledge acquisition
• G06N 5/04 - Inference or reasoning models

Abstract

A method performed by a computing device includes determining a set of identigens for each word of words of a subjective query to produce sets of identigens. The method further includes interpreting, using identigen pairing rules of a knowledge database, the sets of identigens to determine a most likely meaning interpretation of the subjective query and produce a query entigen group that includes query entigens. The method further includes identifying one or more characteristic entigen categories for a subjective category entigen of the query entigen group. The method further includes recovering a set of response entigens for the subjective query from the knowledge database utilizing the query entigen group and based on the one or more characteristic entigen categories. The set of response entigens provides an answer for the subjective query.

IPC Classes  ?

• G06F 40/30 - Semantic analysis
• G06F 16/33 - Querying
• G06F 16/338 - Presentation of query results
• G06F 40/279 - Recognition of textual entities

Abstract

A method performed by a computing device includes obtaining impaired content for a topic that includes a series of words, and determining a set of identigens for each word of the series of words to produce sets of identigens. The method further includes interpreting, using identigen pairing rules of a knowledge database, the sets of identigens to determine a most likely meaning interpretation of the impaired content and produce an interim entigen group. The method further includes recovering an improved entigen group for the topic from the knowledge database utilizing the interim entigen group and based on a knowledge defect of the interim entigen group caused by an impairment of the impaired content.

IPC Classes  ?

• G06F 16/215 - Improving data qualityData cleansing, e.g. de-duplication, removing invalid entries or correcting typographical errors
• G06F 16/28 - Databases characterised by their database models, e.g. relational or object models
• G06F 16/3329 - Natural language query formulation
• G06F 16/3332 - Query translation
• G06F 16/334 - Query execution
• G06F 40/242 - Dictionaries
• G06F 40/247 - ThesaurusesSynonyms
• G06F 40/30 - Semantic analysis

Abstract

A method includes determining a set of identigens for words of content to produce a sets of identigens and interpreting the sets of identigens to determine a most likely meaning interpretation of the content and produce a baseline entigen group. The method further includes recovering an incomplete entigen group for the topic from a first knowledge database based on a knowledge defect of the incomplete entigen group with regards to the topic. The method further includes obtaining an additive entigen group from a second knowledge database based on the knowledge defect and modifying the incomplete entigen group utilizing the additive entigen group to produce an updated entigen group to provide a beneficial cure for the knowledge defect of the incomplete entigen group.

IPC Classes  ?

• G06F 40/30 - Semantic analysis
• G06N 5/02 - Knowledge representationSymbolic representation
• G06F 40/279 - Recognition of textual entities

Abstract

A method includes detecting an incomplete entigen group within a knowledge database. The incomplete entigen group includes entigens and one or more entigen relationships between at least some of the entigens. The incomplete entigen group represents knowledge of a topic. The method further includes obtaining additive content for the topic based on the incomplete entigen group and generating an additive entigen group based on the additive content. The method further includes updating the incomplete entigen group utilizing the additive entigen group to produce an updated entigen group. The method further includes indicating that the updated entigen group has an un-curated status when the additive entigen group conflicts with the incomplete entigen group.

IPC Classes  ?

• G06F 40/30 - Semantic analysis

Abstract

A method executed by a computing device includes determining to update an entigen group within a knowledge database, where the entigen group includes a set of linked entigens that represent knowledge associated with an object. The method further includes determining a set of identigens for each word of a phrase associated with the object to produce sets of identigens. The method further includes interpreting the sets of identigens to determine a most likely meaning interpretation of the phrase and produce a new entigen group. The method further includes updating the entigen group utilizing the new entigen group to produce a curated entigen group such that a deficiency of the entigen group is resolved providing more accurate and more complete knowledge of the object.

IPC Classes  ?

• G06F 40/30 - Semantic analysis
• G06F 16/36 - Creation of semantic tools, e.g. ontology or thesauri
• G06N 5/02 - Knowledge representationSymbolic representation

Abstract

A method executed by a computing device includes determining a set of identigens for a query to produce sets of identigens. A set of identigens of the sets of identigens represents one or more different meanings of a query word of the query. The method further includes interpreting, based on identigen pairing rules of a knowledge database, pairs of sequentially adjacent identigens of adjacent sets of identigens of the sets of identigens to determine a first most likely meaning interpretation of the query and produce a first query entigen group of query entigen groups. The method further includes identifying an inconsistency between at least two query entigen groups of the query entigen groups and obtaining an inconsistency clarification based on the inconsistency. The method further includes selecting one query entigen group of the query entigen groups based on the inconsistency clarification to produce a final query entigen group.

IPC Classes  ?

• G06F 16/242 - Query formulation
• G06F 16/2455 - Query execution
• G06F 16/28 - Databases characterised by their database models, e.g. relational or object models
• G06F 40/289 - Phrasal analysis, e.g. finite state techniques or chunking

Abstract

A computer-implemented method includes determining a set of identigens for each word of patent claim elements to produce sets of identigens and interpreting pairs of adjacent identigens of adjacent sets of identigens to determine a most likely meaning of the claim elements and produce a claim entigen group. The method further includes determining a level of match between the claim entigen group and a comparison matter entigen group. When the level of match between the claim entigen group and the comparison matter entigen group is greater than a threshold level, the method further includes indicating potential utilization of the claim by the comparison matter or potential prior art status of the comparison matter.

IPC Classes  ?

• G06F 17/00 - Digital computing or data processing equipment or methods, specially adapted for specific functions
• G06F 40/237 - Lexical tools
• G06F 40/30 - Semantic analysis
• G06F 16/33 - Querying
• G06N 5/022 - Knowledge engineeringKnowledge acquisition
• G06F 16/35 - ClusteringClassification

Abstract

A computer-implemented method includes determining a set of identigens for each word of a query to produce sets of identigens and interpreting pairs of adjacent identigens of adjacent sets of identigens to determine a most likely meaning of the query and produce a query entigen group. The method further includes identifying entigens of a knowledge database that compare favorably to the query entigen group to produce an initial entigen group and determining whether the initial entigen group requires one or more future available entigens to provide a complete response to the query. When required, the method further includes creating the one or more future available entigens based on obtained targeted data, adding the one or more future available entigens to the initial entigen group to produce an updated entigen group, and outputting the complete response based on the updated entigen group.

IPC Classes  ?

• G06F 17/00 - Digital computing or data processing equipment or methods, specially adapted for specific functions
• G06F 16/245 - Query processing
• G06F 16/28 - Databases characterised by their database models, e.g. relational or object models
• G06F 16/248 - Presentation of query results

Abstract

A method executed by a computing device includes determining a set of identigens for each query word of a query to produce sets of identigens. A set of identigens of the sets of identigens represents one or more different meanings of a query word of the query. The method further includes determining that a first query word is associated with a first query command and determining whether to select the first query command or an identigen of a first set of identigens. When selecting the first query command, the method further includes interpreting remaining sets of identigens to produce a query entigen group that represents a most likely meaning interpretation of remaining query words. The method further includes accessing a knowledge database utilizing the query entigen group to obtain entigen information and outputting a response based on the entigen information and the first query command.

IPC Classes  ?

• G06F 16/33 - Querying
• G06F 40/30 - Semantic analysis
• G06N 5/02 - Knowledge representationSymbolic representation

Abstract

A method executed by a computing device includes determining a set of identigens for each phrase word of a phrase to produce sets of identigens. A set of identigens of the sets of identigens represents one or more different meanings of a phrase word of the phrase. The method further includes obtaining inflection information for one or more phrase words of the phrase. The method further includes selecting an identigen of a first set of identigens based on the inflection information to produce a first identigen selection for the first set of identigens having a selected meaning of one or more different meanings of the first phrase word. The method further includes interpreting remaining sets of identigens of the sets of identigens to produce an entigen group so that the entigen group represents a most likely meaning interpretation of the phrase.

IPC Classes  ?

• G06F 40/289 - Phrasal analysis, e.g. finite state techniques or chunking
• G06F 16/33 - Querying
• G06F 16/36 - Creation of semantic tools, e.g. ontology or thesauri
• G06F 40/237 - Lexical tools
• G06F 40/247 - ThesaurusesSynonyms

Abstract

A method executed by a computing device includes determining a set of identigens for each query word of a query to produce sets of identigens, where a set of identigens represents different meanings of a word of the query. The method further includes obtaining a first identigen selection for a first query word from the first set of identigens. The method further includes interpreting, using identigen pairing rules and based on the first identigen selection, the sets of identigens to produce a query entigen group. The method further includes accessing a knowledge database utilizing the query entigen group to produce a response entigen group. The method further includes generating a response to the query using the response entigen group, where the response includes at least one response word.

IPC Classes  ?

• G06F 40/289 - Phrasal analysis, e.g. finite state techniques or chunking
• G06F 40/247 - ThesaurusesSynonyms
• G06F 40/284 - Lexical analysis, e.g. tokenisation or collocates
• G06F 40/30 - Semantic analysis
• G06N 5/022 - Knowledge engineeringKnowledge acquisition
• G06N 5/025 - Extracting rules from data
• G06N 5/04 - Inference or reasoning models

Abstract

A method executed by a computing device includes determining a set of identigens for each word of a query to produce sets of identigens, where a set of identigens represents different meanings of a word of the query. The method further includes interpreting, using identigen pairing rules, the sets of identigens to produce a query entigen group that represents a most likely meaning interpretation of the query. The method further includes identifying common associated entigens of a knowledge database utilizing the query entigen group. The method further includes selecting a first common associated entigen of the common associated entigens utilizing the query entigen group and generating a response entigen group based on the first common associated entigen and the query entigen group. The method further includes generating a response to the query utilizing the response entigen group, where the response includes at least one response word.

IPC Classes  ?

• G06F 40/289 - Phrasal analysis, e.g. finite state techniques or chunking
• G06F 40/247 - ThesaurusesSynonyms
• G06F 40/284 - Lexical analysis, e.g. tokenisation or collocates
• G06N 5/022 - Knowledge engineeringKnowledge acquisition
• G06N 5/04 - Inference or reasoning models

Abstract

A method for execution by a computing device includes obtaining a set of media element identigens for media elements of media to produce sets of media element identigens. The sets of media element identigens are possible interpretations of a media element. The method further includes generating a set of relationships between media elements. The relationships provide a list of one or more ways in which the media elements are related. The method further includes processing different permutations of the sets of media element identigens using the set of relationships to generate an entigen group. The entigen group represents a most likely interpretation of the media.

IPC Classes  ?

• G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
• A01G 3/00 - Cutting implements specially adapted for horticultural purposesDelimbing standing trees
• A01G 5/00 - Floral handling
• A23N 15/00 - Machines or apparatus for other treatment of fruits or vegetables for human purposesMachines or apparatus for topping or skinning flower bulbs
• G06T 7/11 - Region-based segmentation
• G06T 7/70 - Determining position or orientation of objects or cameras

Abstract

A method executed by a computing device includes determining a set of identigens for each query word of a query to produce sets of identigens. The method further includes interpreting the sets of identigens to produce different first and second query entigen groups. The method further includes generating an interim response based on the first and second query entigen groups. The method further includes determining a set of identigens for each updated query word of an updated query to produce updated sets of identigens. The method further includes selecting one of the first or second query entigen group based on the updated sets of identigens to produce a selected query entigen group. The method further includes generating a response entigen group utilizing the selected query entigen group and generating a response to the query utilizing the response entigen group.

IPC Classes  ?

• G06F 16/00 - Information retrievalDatabase structures thereforFile system structures therefor
• G06F 16/332 - Query formulation
• G06F 40/284 - Lexical analysis, e.g. tokenisation or collocates
• G06F 40/30 - Semantic analysis
• G06N 5/04 - Inference or reasoning models
• G06N 5/022 - Knowledge engineeringKnowledge acquisition

Abstract

A method includes a computing device verifying authenticity of a blockchain-encoded record representing a statement of words and an entigen group to produce an authenticity indicator where a set of identigens is determined utilizing a knowledge database for each word to produce sets of identigens and where the sets of identigens is interpreted to produce the entigen group. When the authenticity indicator indicates an authentic status, the method further includes determining, based on an updated knowledge database, an updated set of identigens for each word of the statement to produce updated sets of identigens. The method further includes interpreting, based on the updated knowledge database, the updated sets of identigens to produce an updated entigen group. The method further includes updating the blockchain-encoded record to represent the statement and the updated entigen group to facilitate subsequent utilization of an updated validated interpretation of the statement as the updated entigen group.

IPC Classes  ?

• H04L 9/32 - Arrangements for secret or secure communicationsNetwork security protocols including means for verifying the identity or authority of a user of the system
• H04L 9/08 - Key distribution
• H04L 9/06 - Arrangements for secret or secure communicationsNetwork security protocols the encryption apparatus using shift registers or memories for blockwise coding, e.g. D.E.S. systems
• H04L 9/00 - Arrangements for secret or secure communicationsNetwork security protocols

Abstract

A method executed by a computing device includes obtaining a string of words and determining whether two or more words of the string of words are in a word group. When the two or more words are in the word group, the method further includes determining a set of identigens for each word of the word group to produce sets of identigens, where a set of identigens of the sets of identigens represents one or more different meanings of a word of the word group. The method further includes interpreting, using identigen pairing rules, the sets of identigens to produce an entigen group. The method further includes assigning a new entigen to represent the entigen group, where the new entigen represents a most likely meaning interpretation of the word group.

IPC Classes  ?

• G06F 17/00 - Digital computing or data processing equipment or methods, specially adapted for specific functions
• G06F 16/23 - Updating
• G06F 16/248 - Presentation of query results
• G06F 16/2457 - Query processing with adaptation to user needs
• G06F 16/2452 - Query translation

Abstract

A method for execution by a computing device includes obtaining a phrase that includes string of words and generating a valid sequence of words utilizing the phrase. The method further includes identifying a set of identigens for each word of the valid sequence of words to produce sets of identigens. The method further includes identifying, for each identigen of the sets of identigens, a word type associated with phrase structure grammar rules to produce sets of identigen-type associations. The method further includes interpreting, utilizing the phrase structure grammar rules, the sets of identigen-type associations to produce an entigen group. The entigen group represents a most likely interpretation of the phrase.

IPC Classes  ?

• G06F 40/284 - Lexical analysis, e.g. tokenisation or collocates
• G06F 16/9032 - Query formulation
• G06F 16/903 - Querying
• G06F 40/253 - Grammatical analysisStyle critique

Abstract

A method includes generating a query entigen group for a query in accordance with identigen rules. The query entigen group represents a most likely interpretation of the query. The method further includes obtaining an embellished entigen group from a knowledge database based on the query entigen group. The embellished entigen group substantially includes the query entigen group and a set of embellishing entigens. The method further includes selecting a set of response entigens from the embellished entigen group in accordance with a response embellishment approach to produce a response entigen group. The set of response entigens includes at least one embellishing entigen of the set of embellishing entigens. The method further includes generating a response phrase based on the response entigen group. The response entigen group represents a most likely interpretation of the response phrase.

IPC Classes  ?

• G06F 16/903 - Querying
• G06N 5/02 - Knowledge representationSymbolic representation

Abstract

A method performed by a computing device includes generating a comparative query entigen group set based on a comparative query in accordance with identigen rules, where the comparative query entigen group set represents a most likely interpretation of the comparative query. The method further includes obtaining a first response entigen group from a knowledge database based on a first comparative query entigen group of the comparative query entigen group set, where the first response entigen group substantially includes the first comparative query entigen group. The method further includes obtaining a second response entigen group from the knowledge database based on a second comparative query entigen group of the comparative query entigen group set, where the second response entigen group substantially includes the second comparative query entigen group. The method further includes generating a comparative response based on the first response entigen group and the second response entigen group.

IPC Classes  ?

• G06F 17/30 - Information retrieval; Database structures therefor
• G06N 5/025 - Extracting rules from data
• G06F 16/903 - Querying
• G06F 16/245 - Query processing
• G06F 16/2455 - Query execution
• G06F 16/2457 - Query processing with adaptation to user needs

Abstract

A method performed by a computing device includes generating a first aptitude level entigen group for a first aptitude level phrase in accordance with identigen rules. The first aptitude level entigen group represents a most likely interpretation of the first aptitude level phrase. The method further includes obtaining a multiple aptitude level entigen group from a knowledge database based on the first aptitude level entigen group. The multiple aptitude level entigen group includes the first aptitude level entigen group. The method further includes generating a second aptitude level entigen group utilizing the multiple aptitude level entigen group. The method further includes generating a second aptitude level phrase based on the second aptitude level entigen group. The second aptitude level entigen group represents a most likely interpretation of the second aptitude level phrase.

IPC Classes  ?

• G06F 16/31 - IndexingData structures thereforStorage structures
• G06F 40/284 - Lexical analysis, e.g. tokenisation or collocates
• G06F 40/30 - Semantic analysis
• G06F 40/53 - Processing of non-Latin text
• G06F 16/33 - Querying
• G06F 40/242 - Dictionaries
• G06N 5/02 - Knowledge representationSymbolic representation
• G06F 40/247 - ThesaurusesSynonyms

Abstract

A method performed by a computing device includes identifying a first set of sentiment identigens of a plurality of sets of identigens for a query that includes a string of words, where the first set of sentiment identigens represents different meanings of a first sentiment word of the string of words. The method further includes selecting an entigen group from a knowledge database based on the plurality of sets of identigens, where a first sentiment entigen of the entigen group corresponds to the first set of sentiment identigens. The method further includes generating a response entigen group based on the entigen group, where a response entigen of the response entigen group corresponds to a selected identigen from a set of identigens of the plurality of sets of identigens regarding a word of the string of words.

IPC Classes  ?

• G06F 40/30 - Semantic analysis
• G06F 40/205 - Parsing
• G06N 5/02 - Knowledge representationSymbolic representation

Abstract

A method performed by a computing device includes obtaining a set of image segment identigens for image segments of an image to produce sets of image segment identigens. A set of image segment identigens is a set of possible interpretations of a first image segment of the image segments. The method further includes identifying a subset of valid image segment identigens of each set of image segment identigens by applying identigen rules to the sets of image segment identigens to produce subsets of valid image segment identigens. Each valid image segment identigen of a subset of valid image segment identigens represents a most likely interpretation of a corresponding image segment. The method further includes generating an image entigen group utilizing the subsets of valid image segment identigens, where the image entigen group represents a most likely interpretation of the image.

IPC Classes  ?

• G06V 10/00 - Arrangements for image or video recognition or understanding
• G06F 16/583 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
• G06T 7/10 - SegmentationEdge detection
• G06K 9/62 - Methods or arrangements for recognition using electronic means
• G06F 16/538 - Presentation of query results
• G06V 10/44 - Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersectionsConnectivity analysis, e.g. of connected components

Abstract

A method includes detecting a defective entigen group within a knowledge database. The defective entigen group includes entigens and one or more entigen relationships between at least some of the entigens. The defective entigen group represents knowledge of a topic. The method further includes obtaining corrective content for the topic based on the defective entigen group and generating a corrective entigen group based on the corrective content. The method further includes updating the defective entigen group utilizing the corrective entigen group to produce a curated entigen group.

IPC Classes  ?

• G06F 40/242 - Dictionaries
• G06N 5/02 - Knowledge representationSymbolic representation
• G06F 16/9035 - Filtering based on additional data, e.g. user or group profiles
• G06F 40/247 - ThesaurusesSynonyms
• G06F 40/289 - Phrasal analysis, e.g. finite state techniques or chunking

Abstract

A method includes identifying a set of identigens for each word of a first phrase of a phrase group to produce a first plurality of sets of identigens and determining whether first and second identigen rules are applicable to the first plurality of sets of identigens. When the first and second identigen rules are applicable to the first plurality of sets of identigens, the method further includes identifying a set of identigens for each word of a second phrase of the phrase group to produce a second plurality of sets of identigens and determining that the first identigen rules are applicable to the second plurality of sets of identigens. The method further includes identifying one valid identigen of each set of identigens of the first plurality of sets of identigens by applying the first identigen rules to the first plurality of sets of identigens to produce a first entigen group.

IPC Classes  ?

• G06F 40/30 - Semantic analysis
• G06F 40/253 - Grammatical analysisStyle critique

Abstract

A method includes identifying identigens for each word of a trusted phrase, where the identigens of a first word of the trusted phrase includes one or more different meanings of the first word. The method further includes identifying two adjacent words of the trusted phrase that are lacking an identigen pairing and determining whether the identigen pairing can be inferred for the two adjacent words based on known identigen pairings of other words of the trusted phrase. When the identigen pairing can be inferred for the two adjacent words, the method further includes adding to a knowledge database the identigen pairing of the two adjacent words.

IPC Classes  ?

• G06F 40/284 - Lexical analysis, e.g. tokenisation or collocates
• G06F 16/903 - Querying
• G06F 16/906 - ClusteringClassification
• G06F 40/205 - Parsing
• G06N 5/04 - Inference or reasoning models

Abstract

A method includes generating an initial entigen group for a query from existing entigens in a knowledge database and determining whether the initial entigen group provides a reliable response to the query. When the initial entigen group does not provide a reliable response to the query, the method further includes determining a desired entigen to add to the initial entigen group to produce an updated entigen group that leads to the reliable response to the query and creating the desired entigen based on obtained targeted data. The method further includes adding the desired entigen to the initial entigen group to produce the updated entigen group and determining whether the updated entigen group provides the reliable response to the query. When the updated entigen group provides the reliable response to the query, the method further includes outputting the reliable response.

IPC Classes  ?

• G06F 17/00 - Digital computing or data processing equipment or methods, specially adapted for specific functions
• G06F 16/245 - Query processing
• G06F 16/28 - Databases characterised by their database models, e.g. relational or object models
• G06F 16/248 - Presentation of query results

Abstract

A method includes obtaining an initial answer entigen group from a knowledge database based on a query entigen group of a query. The method further includes determining that a reliable and definitive answer for the query is not obtainable from the initial answer entigen group. When an incomplete answer entigen is a cause for the inability to obtain the reliable and definitive answer, the method further includes determining a missing element, obtaining data regarding the missing element, updating the incomplete answer entigen with the data to produce an updated answer entigen, and updating the initial answer entigen group with the updated answer entigen to produce an updated answer entigen group. When the updated answer entigen group produces the reliable and definitive answer, the method further includes outputting the reliable and definitive answer.

IPC Classes  ?

• G06F 17/00 - Digital computing or data processing equipment or methods, specially adapted for specific functions
• G06F 16/23 - Updating
• G06F 16/248 - Presentation of query results
• G06F 16/2457 - Query processing with adaptation to user needs
• G06F 16/2452 - Query translation

Abstract

A method includes obtaining a set of image segment identigens for each image segment of an image to produce sets of image segment identigens. The sets of image segment identigens are possible interpretations of an image segment. The method further includes generating a set of relationships between image segments. The relationships provide a list of one or more ways in which the image segments are related. The method further includes processing different permutations of the sets of image segment identigens in accordance with the set of relationships to generate an entigen group. The entigen group represents a most likely interpretation of the image.

IPC Classes  ?

• G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
• G06T 7/11 - Region-based segmentation
• G06T 7/70 - Determining position or orientation of objects or cameras
• G06K 9/64 - Methods or arrangements for recognition using electronic means using simultaneous comparisons or correlations of the image signals with a plurality of references, e.g. resistor matrix
• G06K 9/46 - Extraction of features or characteristics of the image
• G06K 9/62 - Methods or arrangements for recognition using electronic means

Abstract

A method includes generating a new entigen group regarding trusted new information. The method further includes generating entigen groups from phrases of a document and determining whether an entigen group of the entigen groups has a most likely meaning similar to a most likely meaning of the new entigen group. When the entigen group has a most likely meaning similar to the most likely meaning of the new entigen group, the method further includes updating the entigen group based on the new entigen group. When the entigen groups do not include an entigen group having a most likely meaning similar to the most likely meaning of the new entigen group, the method further includes updating the entigen groups to include the new entigen group.

IPC Classes  ?

• G06F 40/30 - Semantic analysis
• G06F 40/289 - Phrasal analysis, e.g. finite state techniques or chunking
• G06F 16/33 - Querying
• G06F 40/284 - Lexical analysis, e.g. tokenisation or collocates

Abstract

A method includes obtaining a string of words and determining whether two or more words of the string of words are in a word group. When the two or more words are in the word group, the method further includes retrieving a set of word group identigens for the word group and retrieving sets of word identigens for remaining words of the string of words. The method further includes determining whether a word group identigen of the set of word group identigens and word identigens of the sets of word identigens creates an entigen group that is a valid interpretation of the string of words. When the entigen group is the valid interpretation of the string of words, the method further includes outputting the entigen group.

IPC Classes  ?

• G06F 40/30 - Semantic analysis
• G06F 40/289 - Phrasal analysis, e.g. finite state techniques or chunking
• G06F 40/284 - Lexical analysis, e.g. tokenisation or collocates
• G06F 16/33 - Querying

Abstract

A method includes generating entigen groups from phrases of a related topic, where the entigen groups represents most likely meanings of the phrases. The method further includes identifying a first entigen group and a second entigen group, where a first meaning of the first entigen group is similar to, but not identical to, a second meaning of the second entigen group. The method further includes determining a meaning difference between the first meaning and the second meaning. When the first meaning has priority over the second meaning, the method further includes updating the second entigen group with the meaning difference to produce an updated second entigen group. When the second meaning has priority over the first meaning, the method further includes updating the first entigen group with the meaning difference to produce an updated first entigen group.

IPC Classes  ?

• G06F 40/284 - Lexical analysis, e.g. tokenisation or collocates
• G06F 40/30 - Semantic analysis
• G06F 40/45 - Example-based machine translationAlignment
• G06F 40/289 - Phrasal analysis, e.g. finite state techniques or chunking

Abstract

A method includes generating a plurality of entigen groups from a set of phrases of a statement and identifying two plausible entigen groups based on a true meaning interpretation of the statement. The method further includes identifying a related entigen group based on a phrase of the statement and interpreting each of the two plausible entigen groups in light of the related entigen group to determine whether one of the two plausible entigen groups is a more likely interpretation of the statement than the other one of the two plausible entigen groups. When the one of the two plausible entigen groups is the more likely interpretation of the statement, the method further includes updating the one of the two plausible entigen groups using the related entigen group to produce an updated entigen group and adding the statement as the updated entigen group to a knowledge database.

IPC Classes  ?

• G06F 40/284 - Lexical analysis, e.g. tokenisation or collocates
• G06F 40/30 - Semantic analysis
• G06F 40/45 - Example-based machine translationAlignment
• G06F 40/289 - Phrasal analysis, e.g. finite state techniques or chunking

Abstract

A method includes generating a plurality of entigen groups from a plurality of phrases, where the plurality of entigen groups represents a plurality of most likely meanings for the plurality of phrases. The method further includes determining an initial interpretation of the related topic based on the plurality of most likely meanings for the plurality of phrases and generating a plurality of scores for the plurality of entigen groups based on the initial interpretation and source information of the plurality of phrases. The method further includes interpreting the plurality of scores in relation to the initial interpretation to determine a confidence level of the initial interpretation and when the confidence level of the initial interpretation compares favorably to a confidence threshold, indicating that the initial interpretation is reliable.

IPC Classes  ?

• G06F 16/31 - IndexingData structures thereforStorage structures
• G06F 40/58 - Use of machine translation, e.g. for multi-lingual retrieval, for server-side translation for client devices or for real-time translation
• G06F 17/18 - Complex mathematical operations for evaluating statistical data
• G06N 5/02 - Knowledge representationSymbolic representation
• G06F 40/30 - Semantic analysis
• G06F 40/289 - Phrasal analysis, e.g. finite state techniques or chunking

Abstract

A method includes interpreting sets of first language identigens to produce an entigen group which represents a most likely meaning of a string of first language words. The method further includes identifying, for each entigen of the entigen group, a corresponding set of second language identigens to identify sets of second language identigens. The method further includes selecting, for each entigen of the entigen group, a selected second language identigen from the corresponding set of second language identigens based on meaning of the entigen to produce an initial string of second language words.

IPC Classes  ?

• G06F 40/58 - Use of machine translation, e.g. for multi-lingual retrieval, for server-side translation for client devices or for real-time translation
• G06F 40/30 - Semantic analysis
• G06F 40/289 - Phrasal analysis, e.g. finite state techniques or chunking
• G06F 40/268 - Morphological analysis
• G06F 40/45 - Example-based machine translationAlignment
• G06F 40/47 - Machine-assisted translation, e.g. using translation memory
• G06F 16/31 - IndexingData structures thereforStorage structures
• G06F 17/18 - Complex mathematical operations for evaluating statistical data
• G06N 5/02 - Knowledge representationSymbolic representation

Abstract

A method includes determining a set of identigens for each word of at least some words of a string of words of a query to produce a plurality of sets of identigens. The method further includes interpreting, based on a first knowledge database, the plurality of sets of identigens to produce a first entigen group and generating a first preliminary query response based on the first entigen group. The method further includes interpreting, based on a second knowledge database, the plurality of sets of identigens to produce a second entigen group and generating a second preliminary query response based on the second entigen group. The method further includes comparing the first and second preliminary query responses and when the first preliminary query response and the second preliminary query response are divergent, resolving inconsistencies between the first and second preliminary query responses to produce a final query response.

IPC Classes  ?

• G06F 15/16 - Combinations of two or more digital computers each having at least an arithmetic unit, a program unit and a register, e.g. for a simultaneous processing of several programs
• G06F 16/332 - Query formulation
• G06F 16/3332 - Query translation
• G06F 16/334 - Query execution
• G06F 16/338 - Presentation of query results
• G06F 16/353 - ClusteringClassification into predefined classes
• G06F 40/30 - Semantic analysis
• G06N 5/04 - Inference or reasoning models

Abstract

A method includes selecting an entigen group from a knowledge database. The entigen group is a most likely meaning of a phrase of a string of words. An entigen of the entigen group corresponds to a selected identigen from a set of identigens regarding a word of the string of words. The set of identigens represent different meanings of the word. The method further includes identifying other entigen groups of alternate phrases having the most likely meaning from the knowledge database. The alternate phrases are different permutations of the string of words. The method further includes determining a dominant digital representation of a human reaction of the other entigen groups and generating a digital representation of a human reaction for the entigen group based on the dominant digital representation of a human reaction.

IPC Classes  ?

• G06N 5/04 - Inference or reasoning models
• G06F 16/33 - Querying
• G06F 16/35 - ClusteringClassification
• G06F 17/27 - Automatic analysis, e.g. parsing, orthograph correction

Abstract

A method includes obtaining a sequence of words of a query and identifying, for each word of the sequence of words, an identigen subset to produce a plurality of identigen subsets. The method further includes determining, in accordance with grouping rules, a query entigen grouping that includes a sequence of unique entigens, where an entigen of the sequence of unique entigens corresponds to an identigen of a corresponding identigen subset of the plurality of identigen subsets, and where the query entigen grouping corresponds to a meaning of associated with the query. The method further includes identifying a section of a knowledge base that substantially matches the query entigen grouping, where the knowledge base facilitates storage of knowledge as a multitude of entigen groupings. The method further includes determining an answer to the query based on the section of the knowledge base.

IPC Classes  ?

• G06F 40/242 - Dictionaries
• G06F 16/31 - IndexingData structures thereforStorage structures
• G06F 16/33 - Querying
• G06F 40/279 - Recognition of textual entities

Goods & Services

Computer software for creating searchable databases of information and data

Abstract

A system for annotating words of a data corpus based upon attributes, items, and actions with Identigens (IDNs) from a Descriptive Dictionary, pairing the word's or their IDNs based on logical forming rules (CETLO Rules); determining if a selected plurality of paired words or IDNs (CETs) are grammatically and syntactically correct by matching IDNs from each pair of words. Optionally, identifying and annotating the individual entities (Entigens) that words are identifying.

IPC Classes  ?

• G06F 17/27 - Automatic analysis, e.g. parsing, orthograph correction
• G06F 17/30 - Information retrieval; Database structures therefor

Goods & Services

Computer software for creating searchable databases of information and data, all in the field of artificial intelligence

Goods & Services

Computer software for creating searchable databases of information and data

Abstract

A system for annotating words of a data corpus based upon their particular concept and their corresponding grammatical sense with Conceptual Numerical Identifiers (CNIs) from a Conceptual Dictionary, pairing the words based on conceptual inter-relating network (CIRN) rules, and determining if a selected plurality of paired words are grammatically, syntactically, and linguistically correct by matching CNIs from each pair of words.

IPC Classes  ?

• G06F 17/27 - Automatic analysis, e.g. parsing, orthograph correction
• G06F 17/21 - Text processing
• G10L 21/00 - Speech or voice signal processing techniques to produce another audible or non-audible signal, e.g. visual or tactile, in order to modify its quality or its intelligibility
• G10L 25/00 - Speech or voice analysis techniques not restricted to a single one of groups

Abstract

A preferred method for identifying at least one of a grammatical, linguistic and/or conceptual integrity of a data corpus is disclosed. In a preferred method, the associations between several word elements of a data corpus are identified. Then, the word elements experiencing several associations are used for identifying the continuum between associations and the number of word elements involved and/or not involved in the associations which is then used for identifying at least one of a: linguistic, semantic, grammatical, conceptual or other integrity or coherence of the analyzed data corpus, such as a query for optionally displaying a data corpus understanding and/or selecting a particular search behavior or other.

IPC Classes  ?

• G06F 17/27 - Automatic analysis, e.g. parsing, orthograph correction
• G06F 17/21 - Text processing
• G10L 21/00 - Speech or voice signal processing techniques to produce another audible or non-audible signal, e.g. visual or tactile, in order to modify its quality or its intelligibility