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Research on feature-based opinion mining using topic maps

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成果类型:
期刊论文
作者:
Xia, Lixin(夏立新);Wang, Zhongyi*;Chen, Chen;Zhai, Shanshan
通讯作者:
Wang, Zhongyi
作者机构:
[Xia, Lixin; Chen, Chen; Wang, Zhongyi; Zhai, Shanshan] Cent China Normal Univ, Sch Informat Management, Wuhan, Peoples R China.
通讯机构:
[Wang, Zhongyi] C
Cent China Normal Univ, Sch Informat Management, Wuhan, Peoples R China.
语种:
英文
关键词:
Feature extraction;Sentiment classification;Topic map;Feature-based opinion mining
期刊:
ELECTRONIC LIBRARY
ISSN:
0264-0473
年:
2016
卷:
34
期:
3
页码:
435-456
基金类别:
This study is supported by National Social Science Foundation of China: “Research on Multi-granularity Integration Knowledge Services of Digital Library Based on Linked Data” (14CTQ003) and is the major project of National Social Science Foundation of China: “Research on Knowledge Discovery of Internet Resource base on Multi-dimensional Aggregation” (No. 13&ZD183).
机构署名:
本校为第一且通讯机构
院系归属:
信息管理学院
摘要:
Purpose - Opinion mining (OM), also known as "sentiment classification", which aims to discover common patterns of user opinions from their textual statements automatically or semi-automatically, is not only useful for customers, but also for manufacturers. However, because of the complexity of natural language, there are still some problems, such as domain dependence of sentiment words, extraction of implicit features and others. The purpose of this paper is to propose an OM method based on topic maps to solve these problems. Design/methodolog...

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