PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Exploring trends in a topic-based search engine
Wray Buntine, Jukka Perkiö and Sami Perttu
In: WI 2004, 20-24 Sep 2004, Beijing, China.

Abstract

Topic-based search engines are an alternative to simple keyword search engines that are common in today's intranets. Trend analysis is an important research goal for many different industries. The temporal behavior of the topics in a topic model based search engine can be used for trend analysis. We apply a topic model approach to an online financial newspaper data and show that these topics can be used to explore prevailing trends. Furthermore we show these trends are consistent with common understanding.

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EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Computational, Information-Theoretic Learning with Statistics
Natural Language Processing
Information Retrieval & Textual Information Access
ID Code:150
Deposited By:Sami Perttu
Deposited On:31 May 2004