Link prediction by correlation on social network

Md Shafiur Rahman, Leema Rani Dey, Sajal Haider, Md Ashraf Uddin, Manowarul Islam

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

6 Citations (Scopus)

Abstract

In a social network, the topology of the network grows through the formation of the link. the connection between two nodes in a social network indicates a confidence in terms of the similarity of some activities. Generally, a new link in the social network is created from different perspectives such as familiarity, cohesiveness, geographical locations etc. The concept of the link in the social network has been utilized to discover the hidden meaning of different fields such as e-commerce, bioinformatics and information retrieval. The prediction of a new link between two nodes in the social network is normally accomplished based on the nature of the topology and the similarity function among the nodes is defined with the help of the number of common friends. In this paper, we propose two link prediction algorithms: Local Link Prediction Algorithm and Global Link prediction by taking into consideration of user's activities as well as the common friends. We apply two formulas called correlation based cScore and influential score based iScore to measure the similarity between the two predicted nodes. Finally, we analyze the performance of the proposed algorithms by using DBLP, PPI, PB, and USAir data sets and the experimental result attests that our link predicted algorithm outperforms over the existing algorithms.

Original languageEnglish
Title of host publication20th International Conference of Computer and Information Technology, ICCIT 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-6
Number of pages6
Volume2018-January
ISBN (Electronic)9781538611500
DOIs
Publication statusPublished - Feb 5 2018
Event20th International Conference of Computer and Information Technology, ICCIT 2017 - Dhaka, Bangladesh
Duration: Dec 22 2017Dec 24 2017

Other

Other20th International Conference of Computer and Information Technology, ICCIT 2017
CountryBangladesh
CityDhaka
Period12/22/1712/24/17

Keywords

  • Correlation
  • Global Link Prediction
  • GPLA
  • Influential Score
  • Link Prediction
  • LLPA
  • Local Link Prediction
  • Node Activities
  • Social Network

ASJC Scopus subject areas

  • Information Systems
  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Signal Processing

Fingerprint Dive into the research topics of 'Link prediction by correlation on social network'. Together they form a unique fingerprint.

  • Cite this

    Rahman, M. S., Dey, L. R., Haider, S., Uddin, M. A., & Islam, M. (2018). Link prediction by correlation on social network. In 20th International Conference of Computer and Information Technology, ICCIT 2017 (Vol. 2018-January, pp. 1-6). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCITECHN.2017.8281812