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Movie review mining and summarization
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Source Conference on Information and Knowledge Management archive
Proceedings of the 15th ACM international conference on Information and knowledge management table of contents
Arlington, Virginia, USA
SESSION: Mining reviews and blogs table of contents
Pages: 43 - 50  
Year of Publication: 2006
ISBN:1-59593-433-2
Authors
Li Zhuang  Tsinghua University, Beijing, P.R. China
Feng Jing  Microsoft Research Asia, Beijing, P.R. China
Xiao-Yan Zhu  Tsinghua University, Beijing, P.R. China
Sponsors
ACM: Association for Computing Machinery
SIGIR: ACM Special Interest Group on Information Retrieval
SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 52,   Downloads (12 Months): 324,   Citation Count: 12
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ABSTRACT

With the flourish of the Web, online review is becoming a more and more useful and important information resource for people. As a result, automatic review mining and summarization has become a hot research topic recently. Different from traditional text summarization, review mining and summarization aims at extracting the features on which the reviewers express their opinions and determining whether the opinions are positive or negative. In this paper, we focus on a specific domain - movie review. A multi-knowledge based approach is proposed, which integrates WordNet, statistical analysis and movie knowledge. The experimental results show the effectiveness of the proposed approach in movie review mining and summarization.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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CITED BY  13

Collaborative Colleagues:
Li Zhuang: colleagues
Feng Jing: colleagues
Xiao-Yan Zhu: colleagues