A relational model of data for large shared data banks
Communications of the ACM
Propagation of trust and distrust
Proceedings of the 13th international conference on World Wide Web
The Lowell database research self-assessment
Communications of the ACM - Adaptive complex enterprises
Codd's Relational Model of Data and Fuzzy Logic: Comparisons, Observations, and Some New Results
CIMCA '06 Proceedings of the International Conference on Computational Inteligence for Modelling Control and Automation and International Conference on Intelligent Agents Web Technologies and International Commerce
Social and Personal Context Modeling for Contact List Recommendation on Mobile Device
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 03
A phenotype reputation estimation function and its study of resilience to social attacks
Journal of Network and Computer Applications
Factors affecting privacy disclosure on social network sites: an integrated model
Electronic Commerce Research
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Communities are the latest phenomena on the Internet. At the heart of each community lies a social network. In this paper, we show a generalized framework to understand and reason in social networks. Previously, researchers have attempted to use inference-specific type of relationships. We propose a framework to represent and reason with general case of social relationship network in a formal way. We call it relationship algebra. In the paper, we first present this algebra then show how this algebra can be used for various interesting computing on a social network weaved in the virtual communities. We show applications such as determining reviewers in a semi-professional network maintained by conference management systems, finding conflict of interest in a publication system, or to infer various trust relationships in a community of close associates, etc. We also show how future community networks can be used to determine who should be immunized in the case of a contagious disease outbreak and how these networks could be used in crime prevention, etc.