A Hybrid Context Based Approach for Web Information Retrieval

Information retrieval mechanisms from the web are a great need of the hour as the amount of the content is growing dynamically every day. There are many algorithms which have been proposed in literature mainly relying on the output of the search engines. These algorithms are either content based or...

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Bibliographic Details
Published in:International journal of computer applications 2010-01, Vol.10 (7), p.25-28
Main Authors: Banu, W Aisha, Abdul Kader, P Sheikh
Format: Article
Language:English
Subjects:
Algorithms
Clustering
Computer simulation
Information retrieval
Mathematical models
Queries
Search engines
Taxonomy
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Summary:Information retrieval mechanisms from the web are a great need of the hour as the amount of the content is growing dynamically every day. There are many algorithms which have been proposed in literature mainly relying on the output of the search engines. These algorithms are either content based or snippet based and perform a clustered outcome re-ranking of the content for the user. This work proposes a hybrid approach to content clustering that combines the best of the web information retrieval methods and also uses the personal preference information of the users modeling a wide range of contexts. This work introduces a context mechanism of the users in the overall process and presents taxonomy of the methods to organize the output of the search engines. Experimental results are promising and show that this approach has great promise for a wide range of queries.
ISSN:0975-8887
0975-8887
DOI:10.5120/1493-2010