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Opinion mining of customer feedback data on the web
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Conference On Ubiquitous Information Management And Communication archive
Proceedings of the 2nd international conference on Ubiquitous information management and communication table of contents
Suwon, Korea
SESSION: Data mining table of contents
Pages 230-235  
Year of Publication: 2008
ISBN:978-1-59593-993-7
Authors
Dongjoo Lee  Seoul National University, Seoul, Republic of Korea
Ok-Ran Jeong  University of Illinois at Urbana-Champaign, Urbana, IL
Sang-goo Lee  Seoul National University, Seoul, Republic of Korea
Sponsors
SIGKDD: ACM Special Interest Group on Knowledge Discovery in Data
SIGMOD: ACM Special Interest Group on Management of Data
Publisher
ACM  New York, NY, USA
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ABSTRACT

As people leave on the Web their opinions on products and services they have used, it has become important to develop methods of (semi-)automatically classifying and gauging them. The task of analyzing such data, collectively called customer feedback data, is known as opinion mining. Opinion mining consists of several steps, and multiple techniques have been proposed for each step. In this paper, we survey and analyze various techniques that have been developed for the key tasks of opinion mining. On the basis of our survey and analysis of the techniques, we provide an overall picture of what is involved in developing a software system for opinion mining.


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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Collaborative Colleagues:
Dongjoo Lee: colleagues
Ok-Ran Jeong: colleagues
Sang-goo Lee: colleagues