Sentiment Mining in WebFountain

ICDE 2005: 21ST INTERNATIONAL CONFERENCE ON DATA ENGINEERING, PROCEEDINGS(2005)

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摘要
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.
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关键词
wide variety,various end-user application,end-user application,entire document,sentiment miner,subject reference,functional system environment,web service,web page,sentiment mining,corpus-level miner,text analysis,natural language processing,web pages,algorithm design and analysis,information retrieval,application software,opinion mining,data mining,web services,natural languages,information analysis,internet
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