Mobile Recommendation Based on Link Community Detection
Joint Authors
Deng, Kun
Zhang, Jianpei
Yang, Jing
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-08-26
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
Since traditional mobile recommendation systems have difficulty in acquiring complete and accurate user information in mobile networks, the accuracy of recommendation is not high.
In order to solve this problem, this paper proposes a novel mobile recommendation algorithm based on link community detection (MRLD).
MRLD executes link label diffusion algorithm and maximal extended modularity (EQ) of greedy search to obtain the link community structure, and overlapping nodes belonging analysis (ONBA) is adopted to adjust the overlapping nodes in order to get the more accurate community structure.
MRLD is tested on both synthetic and real-world networks, and the experimental results show that our approach is valid and feasible.
American Psychological Association (APA)
Deng, Kun& Zhang, Jianpei& Yang, Jing. 2014. Mobile Recommendation Based on Link Community Detection. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-13.
https://search.emarefa.net/detail/BIM-1048938
Modern Language Association (MLA)
Deng, Kun…[et al.]. Mobile Recommendation Based on Link Community Detection. The Scientific World Journal No. 2014 (2014), pp.1-13.
https://search.emarefa.net/detail/BIM-1048938
American Medical Association (AMA)
Deng, Kun& Zhang, Jianpei& Yang, Jing. Mobile Recommendation Based on Link Community Detection. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-13.
https://search.emarefa.net/detail/BIM-1048938
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1048938