Medallia, Inc.

Andrew Ko

Ji Fang

Pablo Zivic

Yibin Lin

Text clustering includes: identifying, for a set of non-stop words in a text, a corresponding set of related topic clusters relating to the set of non-stop words, the identification being based at least in part on a plurality of topic clusters each comprising a corresponding plurality of topically related words and a corresponding cluster identifier; for non-stop words in the set of non-stop words that are identified to have corresponding related topic clusters, replacing the non-stop words with corresponding cluster identifiers of the corresponding related topic clusters to generate a clustered version of the text; and providing the clustered version of the text to be further analyzed.

Enhanced text clustering based on topic clusters

Context-based sentiment analysis includes: determining whether a piece of comment data included in a comment is context-sensitive, the determination being made with reference to a set of comment features; determining a context sentiment type of an associated context related to the piece of comment data, the associated context being distinct from the comment, in the event that the piece of comment data is determined to be context-sensitive, and the determination being made with reference to at least a set of context features; and classifying the comment data in the event that the piece of comment data is determined to be context-sensitive, the classification being based at least in part on the comment data and the context sentiment type.

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Mountian View, CA, United States of America

Andrew Ko