A Sentiment Classification Method Based on Parts of Speech Combination and Feature Selection
A technology of emotion classification and feature selection, applied in the field of computer science, can solve problems such as fragrant garbage, inability to directly extract, inability to directly learn vectors, etc.
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[0039] The technical solution of the present invention will be described in detail below in conjunction with the accompanying drawings. In this embodiment, the microblog comment text is used as input text data.
[0040] Such as figure 1 , the sentiment classification method based on part-of-speech combination and feature selection of the present embodiment carries out active and negative binary classification to text sentiment, comprises the following steps:
[0041] Step 1) Initialize the word-part-of-speech Word2vec model.
[0042] Step 2) Preprocessing the text, and selecting feature words with emotional information from the preprocessed text data based on the sentiment dictionary. The sentiment dictionary of this embodiment is composed of a basic sentiment dictionary, an extended sentiment dictionary and a multi-collocation sentiment dictionary.
[0043] Step 3) Combine each feature word and part of speech to convert the text into a sequence text of "word part of speech...
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