A METHOD FOR ADAPTIVELY CLASSIFYING SENTIMENT OF DOCUMENT SNIPPETS

摘要

The present invention relates to a method for adaptively classifying sentiment of document snippets, comprising the steps of: crawling Web documents to search document snippets; populating document snippets by entity and using sentiment lexicon to annotate sentiment-bearing snippets; creating initial training data sets from the populated document snippets and building a machine learning model for each initial training data set; classifying sentiment of new document snippets of an entity using the machine learning model from the initial training data sets; characterised by the steps of: inspecting and correcting results of the sentiment classification performed by the machine learning model at a predetermined time interval; adapting the initial training data sets according to the corrected results of the sentiment classification, building a new machine learning model according to the adapted training data sets; and classifying sentiment of new document snippets of an entity adaptively using the adapted training data sets.