Opinion Target Extraction Method with Speech Rules and Dependency Parsing

doi:10.3969/j.issn.1006-2475.2016.04.004

Abstract

Abstract:

Abstract: Extracting opinion targets simultaneously benefit users and businesses, as businesses understand the product features by the opinion target of interest to users, then improve product quality, and users can make purchasing decisions by these objects. Due to the special circumstances of Web reviews, the extraction of opinion targets is more complex than conventional information processing. Based on some scholars’ basic researches, the paper proposed an extracting method for speech rules and dependency parsing. Firstly, speech rule is used to make noun phrase extraction template, getting candidate opinion targets that are filtered for the first time according to the modification of evaluation terms to opinion target. Secondly, eight kinds of dependency relationship are used to filter opinion targets for the second time. Finally, two kinds of screening results are combined to give the final opinion targets. Experimental results demonstrate that this method on three types of data sets has achieved certain results.

Key words: opinion target, evaluation term, information extraction, speech rules, dependency parsing

CLC Number:

TP391

ZHANG Jian-hua1, XIAO Zhong-zheng2.

Opinion Target Extraction Method with Speech Rules and Dependency Parsing[J]. Computer and Modernization, doi: 10.3969/j.issn.1006-2475.2016.04.004.

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