Enhancing Recommendation using Ranking in Multidimensional Space

R  Suganya Devi; A  P  Chitraand D  Manjula

doi:10.17485/ijst/2016/v9i27/89853

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Enhancing Recommendation using Ranking in Multidimensional Space

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Indian Journal of Science and Technology

DOI: 10.17485/ijst/2016/v9i27/89853

Year: 2016, Volume: 9, Issue: 27, Pages: 1-8

Original Article

Enhancing Recommendation using Ranking in Multidimensional Space

R. Suganya Devi^*, A. P. Chitraand D. Manjula

Department of Computer Science and Engineering, [email protected]
[email protected]
[email protected]
*Author for correspondence
Suganya Devi
Department of Computer Science and Engineering,
Email: [email protected]

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

Search engines play their vital part in building ranking algorithms. Product Recommendation systems is a business activity which involves ranking to fulfill customer needs among the competitors. In our work, similar queries are extracted using Memory based Collaborative Filtering (MCF) and those individual ranked lists are combined to produce single superior ranked lists using Top-k Event Scanning (TES) approach, a rank aggregation algorithm which employs B+ trees for indexing. Experimental results shows that the performance is achieved 90% more than the other existing methods.
Keywords: Indexing, Queries, Ranking, Recommendation, Similar, Top-K, Users