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author:

Lai, Taiping (Lai, Taiping.) [1] | Zheng, Xianghan (Zheng, Xianghan.) [2]

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EI Scopus

Abstract:

In view of the problems existing in traditional recommendation algorithm of low accuracy and low efficiency, this paper presents a machine learning based social media recommendation algorithm. The algorithm is based on the traditional personalized collaborative filtering algorithm, and combines with the correlation characteristics among users in a social network. Besides, the algorithm also considers the network rating factors and upgrade its efficiency by using clustering algorithm. At last, the algorithm is realized on the Hadoop cloud platform. © 2015 IEEE.

Keyword:

Clustering algorithms Collaborative filtering Data mining Efficiency Machine learning Social networking (online)

Community:

  • [ 1 ] [Lai, Taiping]College of Mathematics and Computer Science, Fuzhou University, Fuzhou; 350108, China
  • [ 2 ] [Zheng, Xianghan]Fujian Key Laboratory of Network Computing and Intelligent Information Processing, Fuzhou; 350108, China

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Year: 2015

Page: 28-32

Language: English

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 3

ESI Highly Cited Papers on the List: 0 Unfold All

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Chinese Cited Count:

30 Days PV: 1

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