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Erschienen in:
2006 | OriginalPaper | Buchkapitel
CatS: A Classification-Powered Meta-Search Engine
verfasst von : Miloš Radovanović, Mirjana Ivanović
Erschienen in: Advances in Web Intelligence and Data Mining
Verlag: Springer Berlin Heidelberg
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CatS is a meta-search engine that utilizes text classification techniques to improve the presentation of search results. After posting a query, the user is offered an opportunity to refine the results by browsing through a category tree derived from the dmoz Open Directory topic hierarchy. This paper describes some key aspects of the system (including HTML parsing, classification and displaying of results), outlines the text categorization experiments performed in order to choose the right parameters for classification, and puts the system into the context of related work on (meta-)search engines. The approach of using a separate category tree represents an extension of the standard relevance list, and provides a way to refine the search
on need
, offering the user a non-imposing, but potentially powerful tool for locating needed information quickly and efficiently. The current implementation of CatS may be considered a baseline, on top of which many enhancements are possible.