A novel link prediction approach for scale-free networks

Chungmok Lee, Minh Pham, Norman Kim, Myong K. Jeong, Dennis K.J. Lin, Wanpracha Art Chavalitwongse

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Citations (Scopus)

Abstract

The link prediction problem is to predict the existence of a link between every node pair in the network based on the past observed networks arising in many practical applications such as recommender systems, information retrieval, and the marketing analysis of social networks. Here, we propose a new mathematical programming approach for predicting a future network utilizing the node degree distribution identified from historical observation of the past networks. We develop an integer programming problem for the link prediction problem, where the objective is to maximize the sum of link scores (probabilities) while respecting the node degree distribution of the networks. The performance of the proposed framework is tested on the real-life Facebook networks. The computational results show that the proposed approach can considerably improve the performance of previously published link prediction methods.

Original languageEnglish (US)
Title of host publicationWWW 2014 Companion - Proceedings of the 23rd International Conference on World Wide Web
PublisherAssociation for Computing Machinery, Inc
Pages1333-1338
Number of pages6
ISBN (Electronic)9781450327459
DOIs
StatePublished - Apr 7 2014
Event23rd International Conference on World Wide Web, WWW 2014 - Seoul, Korea, Republic of
Duration: Apr 7 2014Apr 11 2014

Publication series

NameWWW 2014 Companion - Proceedings of the 23rd International Conference on World Wide Web

Other

Other23rd International Conference on World Wide Web, WWW 2014
CountryKorea, Republic of
CitySeoul
Period4/7/144/11/14

Fingerprint

Complex networks
Mathematical programming
Recommender systems
Integer programming
Information retrieval
Marketing

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Software

Cite this

Lee, C., Pham, M., Kim, N., Jeong, M. K., Lin, D. K. J., & Chavalitwongse, W. A. (2014). A novel link prediction approach for scale-free networks. In WWW 2014 Companion - Proceedings of the 23rd International Conference on World Wide Web (pp. 1333-1338). (WWW 2014 Companion - Proceedings of the 23rd International Conference on World Wide Web). Association for Computing Machinery, Inc. https://doi.org/10.1145/2567948.2580049
Lee, Chungmok ; Pham, Minh ; Kim, Norman ; Jeong, Myong K. ; Lin, Dennis K.J. ; Chavalitwongse, Wanpracha Art. / A novel link prediction approach for scale-free networks. WWW 2014 Companion - Proceedings of the 23rd International Conference on World Wide Web. Association for Computing Machinery, Inc, 2014. pp. 1333-1338 (WWW 2014 Companion - Proceedings of the 23rd International Conference on World Wide Web).
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Lee, C, Pham, M, Kim, N, Jeong, MK, Lin, DKJ & Chavalitwongse, WA 2014, A novel link prediction approach for scale-free networks. in WWW 2014 Companion - Proceedings of the 23rd International Conference on World Wide Web. WWW 2014 Companion - Proceedings of the 23rd International Conference on World Wide Web, Association for Computing Machinery, Inc, pp. 1333-1338, 23rd International Conference on World Wide Web, WWW 2014, Seoul, Korea, Republic of, 4/7/14. https://doi.org/10.1145/2567948.2580049

A novel link prediction approach for scale-free networks. / Lee, Chungmok; Pham, Minh; Kim, Norman; Jeong, Myong K.; Lin, Dennis K.J.; Chavalitwongse, Wanpracha Art.

WWW 2014 Companion - Proceedings of the 23rd International Conference on World Wide Web. Association for Computing Machinery, Inc, 2014. p. 1333-1338 (WWW 2014 Companion - Proceedings of the 23rd International Conference on World Wide Web).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Lee C, Pham M, Kim N, Jeong MK, Lin DKJ, Chavalitwongse WA. A novel link prediction approach for scale-free networks. In WWW 2014 Companion - Proceedings of the 23rd International Conference on World Wide Web. Association for Computing Machinery, Inc. 2014. p. 1333-1338. (WWW 2014 Companion - Proceedings of the 23rd International Conference on World Wide Web). https://doi.org/10.1145/2567948.2580049