International Business Machines Corporation

Amir Menczel

Noam Slonim

Ranit Aharonov

Yosi Mass

Charles Arthur Jochim

Dafna Sheinwald

Ilya Shnayderman

Roy N Bar-Haim

Orith Toledo-Ronen

Alon Halfon

A method including: generating, from a text corpus, a lexicon of unigrams and bigrams comprising an embedding for each of said unigrams and bigrams; training a machine learning classifier on a training set comprising a subset of said lexicon, wherein each of said unigrams and bigrams in said subset has a sentiment label; applying said machine learning classifier to said lexicon, to (i) predict a sentiment of each of said unigrams and bigrams, and (ii) update said lexicon with the predicted sentiments; and performing statistical analysis on said updated lexicon, to extract one or more sentiment composition lexicons, wherein each of said one or more sentiment composition lexicons is associated with a sentiment composition class.

Learning sentiment composition from sentiment lexicons

A method comprising: operating at least one hardware processor for: receiving, as input, at least one named entity, modifying said named entity based on a plurality of modification rules to generate a set of candidate named entities corresponding to said named entity, and identifying, for at least one candidate named entity in said set of candidate named entities, an article in a knowledge base of articles, wherein a title of said article matches said candidate named entity.

Automated entity disambiguation

Growing community of inventors

Ashdod, Israel

Amir Menczel