Mining and Visualizing Mobile Social Network Based on Bayesian Probabilistic Model

Autor:	Sung-Bae Cho, Jun-Ki Min, Su-Hyung Jang
Rok vydání:	2009
Předmět:	World Wide Web Social computing business.industry Mobile phone Computer science Mobile social network Phone Closeness Bayesian network The Internet business Personally identifiable information
Zdroj:	Ubiquitous Intelligence and Computing ISBN: 9783642028298 UIC
Popis:	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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::abfd2e3582f7e6067156efdeab6ba7a3 https://doi.org/10.1007/978-3-642-02830-4_10 Zobrazit plný text záznamu