Improve and Optimize Query Recommendation System by MST Algorithm and its MapReduce Implementation

Jian Liang Meng; Da Wei Li

doi:10.4028/www.scientific.net/AMM.701-702.50

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 701-702Improve and Optimize Query Recommendation System...

Improve and Optimize Query Recommendation System by MST Algorithm and its MapReduce Implementation

Abstract:

Query recommendation as an important tool to enhance the user search efficiency has gradually become a hotspot. In the context of big data, using the MapReduce programming model, combined with distributed minimum spanning tree algorithm, a parallel query recommended method based on MapReduce was proposed in this paper. The final results show that the efficiency of query recommendation was greatly improved through parallel computing.

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Periodical:

Applied Mechanics and Materials (Volumes 701-702)

Pages:

50-53

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.701-702.50

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Online since:

December 2014

Authors:

Jian Liang Meng, Da Wei Li*

Keywords:

Distribute, Hadoop, MapReduce, MST, Query Recommendation

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* - Corresponding Author

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