Original scientific paper

https://doi.org/10.17559/TV-20150731103906

Efficient optimization for L-extSKY recommendations

Zhenhua Huang ; Department of Computer Science, Tongji University, 4800 Cao'an Hwy, Jiading, Shanghai 201804, China
Juru Wang ; Department of Medical Electronics and Information Engineering, Shanghai Medical Instrumentation College, Shanghai 200093, China
Bo Zhang ; Department of Computer Science, Shanghai Normal University, Shanghai 200234, China

Abstract

L-extSKY recommendation has recently received a lot of attention in information retrieval community. Literature [1] proposes an algorithm EARG (Effi-cient Approach based on Regular Grid) to produce the L-extSKY objects in one single subspace. However, in multi-user environments, the system gener-ally handles multiple subspace L-extSKY recommendations simultaneously. Hence, in this paper, we present an efficient algorithm AOMSR (Algorithm for Optimizing Multiple Subspace L-extSKY Recommendations) to remarkably reduce the total response time. Furthermore, we discuss two interesting variations of L-extSKY recommendation, i.e., global constraint L-extSKY recommendation and local constraint L-extSKY recommendation, which are meaningful in practice, and show how our algorithm can be applied for their efficient processing. Detailed theoretical analyses and extensive experiments that demonstrate our solution are both efficient and effective.

Keywords

information retrieval; L-extSKY recommendation; subspace; performance evaluation

Hrčak ID:

147275

URI

https://hrcak.srce.hr/147275

Publication date:

22.10.2015.

Article data in other languages: croatian

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