Buzzmetrics, Ltd.

International Business Machines Corporation

Buzzmetrics, Ltd an Israel Corporation

Matthew F Hurst

Kamal P Nigam

Tetsuya Nasukawa

The present application presents methods for performing topical sentiment analysis on electronically stored communications employing fusion of polarity and topicality. The present application also provides methods for utilizing shallow NLP techniques to determine the polarity of an expression. The present application also provides a method for tuning a domain-specific polarity lexicon for use in the polarity determination. The present application also provides methods for computing a numeric metric of the aggregate opinion about some topic expressed in a set of expressions.

Topical sentiments in electronically stored communications

A technique for extracting a meaningful text block from a document where a table, an itemized list, a multiple column, etc., are arbitrarily laid out. A document is input which is laid out using blanks or the like, then a symbol is acquired which is associated with a spatial coordinate of the document. Consecutive characters of the same type are extracted from the symbol to generate a token and a space. A stream is generated from consecutive spaces in the column direction, while a text block is generated from streams and tokens. A link is generated between the text blocks to form a document graph. Validity of a connection (link) between the text blocks in the document graph is evaluated using a language model, then the text blocks are merged if the connection is valid.

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Pittsburgh, PA, United States of America

Matthew F Hurst