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International Journal of Computer Applications
Article . 2011 . Peer-reviewed
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Web knowledge and Wordnet based Automatic Web Query Classification

Authors: K. R. Chandran; S. Lovelyn Rose;

Web knowledge and Wordnet based Automatic Web Query Classification

Abstract

search queries are the starting point to access the contents in the WWW for most of the users. Capturing the user intent behind a query statement is crucial for any search engine and is equivalent to figuring out the category to which the query belongs to. In this paper, we analyze a classification system that uses web directory search results as an extended feature of the query. A comparison with glossary based mapping showed that our work outperforms it by a reasonable margin. We also show by experimentation that choosing the right parameter for the search results gives a reasonable improvement in ranking.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
gold