Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 37, 2020 No. 8
2266-2272

Representation for implicit feedback recommender

Mei Lanxianga
Yu Xueb
a. College of Intelligence & Computing, b. College of Management & Economics, Tianjin University, Tianjin 300000, China
DOI: 10.19734/j.issn.1001-3695.2019.02.0063

Abstract

Neighborhood-based top-N recommendation techniques for implicit users' interaction data are ranking models, of which similarity functions are the important ingredients. Traditional similarity functions suffer from two major issues: sparse data and high dimensional data. Sparse data hinder the recommendation system from scoring on smooth neighborhood, high dimensional data causes the curse of dimensionality problem. This paper proposed a representation-based approach named multi object representation learning(MO) for recommendation, MO was a bipartite node representation learning algorithm, which embedded the different level of network structures and item ordering information into nodes representations to help leverage the recommendation performance. Experimental results on three real data sets of different scales show that the algorithm has higher accuracy and recall than the commonly used recommendation model based on implicit feedback, especially for large-scale data sets, which can effectively alleviate the problems of matrix sparsity and dimensionality disaster, and improve the recommended performance.

Foundation Support

国家自然科学基金资助项目(71502125)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2019.02.0063
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 8
Section: Algorithm Research & Explore
Pages: 2266-2272
Serial Number: 1001-3695(2020)08-005-2266-07

Publish History

[2020-08-05] Printed Article

Cite This Article

梅岚翔, 郁雪. 针对隐式反馈推荐系统的表征学习方法 [J]. 计算机应用研究, 2020, 37 (8): 2266-2272. (Mei Lanxiang, Yu Xue. Representation for implicit feedback recommender [J]. Application Research of Computers, 2020, 37 (8): 2266-2272. )

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  • Application Research of Computers Monthly Journal
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Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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