Subjective Relation Extraction in Chinese Opinion Mining
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TL;DR
This method incorporates relation extraction into opinion mining and solves the problem of coreference and omitting of opinion targets to some extent and finds that the intensifiers can improve the performance of subjective relation extraction.
Abstract
This paper presents a novel method to extract the subjective relationship between opinion-bearing terms and opinion targets.This method extracted the pairs of opinion-bearing terms and opinion targets as the candidate set,and then employed the maximum entropy model to combine lexical, part of speech,semantic and positional features derived from text.Our method incorporates relation extraction into opinion mining and solves the problem of coreference and omitting of opinion targets to some extent.The experiments showed that the F value of our method is 15% higher than that of Baseline which takes the nearest opinion target as the real target,Besides,the experiments found that the intensifiers can improve the performance of subjective relation extraction.