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2006
ACM

Categorizing web search results into meaningful and stable categories using fast-feature techniques

9 years 5 months ago
Categorizing web search results into meaningful and stable categories using fast-feature techniques
When search results against digital libraries and web resources have limited metadata, augmenting them with meaningful and stable category information can enable better overviews and support user exploration. This paper proposes six “fast-feature” techniques that use only features available in the search result list, such as title, snippet, and URL, to categorize results into meaningful categories. They use credible knowledge resources, including a US government organizational hierarchy, a thematic hierarchy from the Open Directory Project (ODP) web directory, and personal browse histories, to add valuable metadata to search results. In three tests the percent of results categorized for five representative queries was high enough to suggest practical benefits: general web search (76-90%), government web search (39-100%), and the Bureau of Labor Statistics website (48-94%). An additional test submitted 250 TREC queries to a search engine and successfully categorized 66% of the top ...
Bill Kules, Jack Kustanowitz, Ben Shneiderman
Added 14 Jun 2010
Updated 14 Jun 2010
Type Conference
Year 2006
Where JCDL
Authors Bill Kules, Jack Kustanowitz, Ben Shneiderman
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