Mining and visualizing mobile social network based on bayesian probabilistic model

Jun Ki Min, Su Hyung Jang, Sung Bae Cho

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

6 Citations (Scopus)

Abstract

Social networking has provided powerful new ways to find people, organize groups, and share information. Recently, the potential functionalities of the ubiquitous infrastructure let users form a mobile social network (MSN) which is discriminative against the previous social networks based on the Internet. Since a mobile phone is used in a much wider range of situations and is carried by the user at all times, it easily collects personal information and can be customized to fit the user's preference. In this paper, we presented MSN mining model which estimates the social contexts like closeness and relationship from uncertain phone logs using a Bayesian network. The mining results were then used for recommending callees or representing the state of social relationships. We have implemented the phonebook application that displays the contexts as network or graph style, and have performed a subjectivity test. As a result, we have confirmed that the visualizing of the MSN is useful as an interface for social networking services.

Original languageEnglish
Title of host publicationUbiquitous Intelligence and Computing - 6th International Conference, UIC 2009, Proceedings
Pages111-120
Number of pages10
DOIs
Publication statusPublished - 2009 Nov 9
Event6th International Conference on Ubiquitous Intelligence and Computing, UIC 2009 - Brisbane, QLD, Australia
Duration: 2009 Jul 72009 Jul 9

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5585 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other6th International Conference on Ubiquitous Intelligence and Computing, UIC 2009
CountryAustralia
CityBrisbane, QLD
Period09/7/709/7/9

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All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Min, J. K., Jang, S. H., & Cho, S. B. (2009). Mining and visualizing mobile social network based on bayesian probabilistic model. In Ubiquitous Intelligence and Computing - 6th International Conference, UIC 2009, Proceedings (pp. 111-120). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5585 LNCS). https://doi.org/10.1007/978-3-642-02830-4_10