Abstract

Certain aspects of the disclosure provide a system and method for generating codes associated with clusters of sentiments, comprising receiving a text input, partitioning the text input into one or more segments, generating one or more numerical vectors associated with each of the one or more segments, comparing the one or more numerical vectors to generate a plurality of cosine proximity values associated with the one or more numerical vectors, applying a clustering algorithm to the one or more numerical vectors to generate clusters of segments within one or more cosine proximity ranges, and generating one or more codes associated with each of the clusters of segments within the one or more cosine proximity ranges, wherein each cluster represents an overall sentiment.

IPC Classes  ?

• G06F 18/2325 - Non-hierarchical techniques using vector quantisation
• G06F 18/2413 - Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches based on distances to training or reference patterns
• G06F 40/205 - Parsing
• G06F 8/38 - Creation or generation of source code for implementing user interfaces
• G06F 8/33 - Intelligent editors
• G06Q 30/02 - MarketingPrice estimation or determinationFundraising

Abstract

Certain aspects of the disclosure provide a system and method for generating codes associated with clusters of sentiments, comprising receiving a text input, partitioning the text input into one or more segments, generating one or more numerical vectors associated with each of the one or more segments, comparing the one or more numerical vectors to generate a plurality of cosine proximity values associated with the one or more numerical vectors, applying a clustering algorithm to the one or more numerical vectors to generate clusters of segments within one or more cosine proximity ranges, and generating one or more codes associated with each of the clusters of segments within the one or more cosine proximity ranges, wherein each cluster represents an overall sentiment.

IPC Classes  ?

• G06F 16/35 - ClusteringClassification
• G06F 40/30 - Semantic analysis
• G06F 3/0486 - Drag-and-drop

Abstract

A method of analyzing sentiments includes receiving one or more strings of text, identifying sentiments related to a first topic from the one or more strings of text, and assigning a sentiment score to each of the sentiments related to the first topic, where the sentiment score corresponds to a degree of positivity or negativity of a sentiment of the sentiments. The method further includes calculating an average sentiment score for the first topic based on the sentiment score for each of the sentiments related to the first topic, determining a percentile for the first topic based on a frequency of sentiments related to the first topic, where the percentile for the first topic is determined with respect to a maximum frequency of sentiments related to one or more other topics, and computing an X-Score based on the average sentiment score and the percentile of the first topic.

IPC Classes  ?

• G06F 40/35 - Discourse or dialogue representation
• G06F 17/18 - Complex mathematical operations for evaluating statistical data
• G10L 15/26 - Speech to text systems
• G10L 25/63 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination for estimating an emotional state

Goods & Services

Software as a service (SAAS), namely, computer software in the field of analyzing customer experience data, evaluating customer comments, experience (satisfaction) score computation, and experience (satisfaction) score strategy and management; Software as a service (SAAS), namely, computer software for measuring the experience (satisfaction) to aid in customer management, patient management, and employee management