DocumentCode
2848954
Title
Sentiment mining in WebFountain
Author
Yi, Jeonghee ; Niblack, Wayne
Author_Institution
IBM Almaden Res. Center, San Jose, CA, USA
fYear
2005
fDate
5-8 April 2005
Firstpage
1073
Lastpage
1083
Abstract
WebFountain is a platform for very large-scale text analytics applications that allows uniform access to a wide variety of sources. It enables the deployment of a variety of document-level and corpus-level miners in a scalable manner, and feeds information that drives end-user applications through a set of hosted Web services. Sentiment (or opinion) mining is one of the most useful analyses for various end-user applications, such as reputation management. Instead of classifying the sentiment of an entire document about a subject, our sentiment miner determines sentiment of each subject reference using natural language processing techniques. In this paper, we describe the fully functional system environment and the algorithms, and report the performance of the sentiment miner. The performance of the algorithms was verified on online product review articles, and more general documents including Web pages and news articles.
Keywords
Internet; data mining; information retrieval; natural languages; text analysis; Web service; WebFountain; corpus-level miner; document-level miner; end-user application; natural language processing; online product review article; reputation management; sentiment mining; text analytics application; Algorithm design and analysis; Application software; Data mining; Feeds; Information analysis; Large-scale systems; Natural language processing; Performance analysis; Web pages; Web services;
fLanguage
English
Publisher
ieee
Conference_Titel
Data Engineering, 2005. ICDE 2005. Proceedings. 21st International Conference on
ISSN
1084-4627
Print_ISBN
0-7695-2285-8
Type
conf
DOI
10.1109/ICDE.2005.132
Filename
1410217
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