Language and sentiment analysis for generating support summaries
AssigneeInsight Direct USA, Inc.
InventorsJason Rader, David McCurdy
Life of this patent
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Abstract
A method of generating a support summary includes extracting chat information including natural language data from a support chat with a user. Tokenized language is generated by performing feature extraction on this natural language data. This tokenized language is subjected to sentiment analysis to produce sentiment data reflecting sentiment of the support user during the support chat, and to semantic analysis to extract support-relevant features. A support summary made up of natural language text identifying a support issue and information germane to the support issue is then generated from the extracted chat information using a language model, at least in part from the extracted support-relevant features and the sentiment data.
Claims20
A method of generating a support summary, the method comprising:
- extracting chat information from a support chat with a support user via a processor, the chat information including natural language data;
- tokenizing the natural language data to generate tokenized language;
- performing sentiment analysis on the tokenized language to produce sentiment data reflecting sentiment of the support user during the support chat;
- performing semantic analysis on the tokenized language to extract support-relevant features;
- producing the support summary using a language model, wherein:
- the support summary comprises a natural language text identifying a support issue and information germane to the support issue, from the extracted chat information;
- and
- the language model produces the support summary at least in part from the extracted support-relevant features and the sentiment data.
A system for generating a support summary from a natural language chat record of a support interaction with a support user, the support summary comprising natural language text identifying a support issue and information germane to the support issue, the system comprising:
- a tokenization module configured to tokenize the natural language chat record;
- a sentiment identification module configured to produce sentiment data from the tokenized natural language chat record, the sentiment data reflecting sentiment of the support user during the support interaction;
- a semantic analysis module configured to extract support-relevant features from the tokenized natural language chat record;
- and
- a language model configured to generate the support summary from the support-relevant features and the sentiment data.
Dependencies are inferred from the claim text.