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author:

Lai, T. (Lai, T..) [1] | Zheng, X. (Zheng, X..) [2]

Indexed by:

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; Collaborative Filtering; MapReduce; Recommendation; Social Network

Community:

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

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Source :

ICSDM 2015 - Proceedings 2015 2nd IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services

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

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 6

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