Regression recommendation algorithm based on extreme learning machine and nearest neighbors

doi:10.3969/j.issn.1000-1565.2017.06.014

Journal of Hebei University (Natural Science Edition) ›› 2017, Vol. 37 ›› Issue (6): 662-666.DOI: 10.3969/j.issn.1000-1565.2017.06.014

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Regression recommendation algorithm based on extreme learning machine and nearest neighbors

CHEN Aixia¹,LI Ning²

1.College of Mathematics and Information Science, Hebei University, Baoding 071002, China; 2.Institute of Information Engineering, Chinese Academy of Sciences, Beijing 100093, China

Received:2016-11-08 Published:2017-11-25

Abstract

Abstract: This paper proposed a collaborative filtering regression recommendation algorithm based on extreme learning machine(ELM)and nearest neighbors.The algorithm firstly used the k nearest neighbors method to fill the missing attribute value,then the ELM regression machine is used to produce recommendations for the user.On the benchmarking data sets in the field of recommendation,we compared our algorithm with the common recommend algorithm—LRCF algorithm,and verified the effectiveness of the proposed algorithm.

Key words: k nearest neighbors, extreme learning machine, recommender systems

CLC Number:

TP183

CHEN Aixia,LI Ning. Regression recommendation algorithm based on extreme learning machine and nearest neighbors[J]. Journal of Hebei University (Natural Science Edition), 2017, 37(6): 662-666.

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Regression recommendation algorithm based on extreme learning machine and nearest neighbors

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