Query Recommendation Based on Document Content User Focuses on

Bo Zhang; Feng Ze Yang; Li Nan Fan

doi:10.4028/www.scientific.net/AMM.511-512.385

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 511-512Query Recommendation Based on Document Content...

Query Recommendation Based on Document Content User Focuses on

Abstract:

To the problem of text elements outside main content of clicked documents have big negative impact on the precision of query recommendation, this paper proposed a query recommendation method based on document content user focuses on, which fused similarity computation among queries with the filter of text elements outside main content of clicked documents. Experimental result shows that the method proposed by this paper can raise the precision of similarity computation among queries, and then raise the precision of query recommendation.

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Periodical:

Applied Mechanics and Materials (Volumes 511-512)

Pages:

385-388

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.511-512.385

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Online since:

February 2014

Authors:

Bo Zhang*, Feng Ze Yang, Li Nan Fan

Keywords:

Entropy Model, Irrelevant Term Filtering, Query Log Mining, Query Recommendation

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* - Corresponding Author

References

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