A logic for uncertain probabilities
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Trust network analysis with subjective logic
ACSC '06 Proceedings of the 29th Australasian Computer Science Conference - Volume 48
Extracting product features and opinions from reviews
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
A holistic lexicon-based approach to opinion mining
WSDM '08 Proceedings of the 2008 International Conference on Web Search and Data Mining
Optimal Trust Network Analysis with Subjective Logic
SECURWARE '08 Proceedings of the 2008 Second International Conference on Emerging Security Information, Systems and Technologies
Mining opinion features in customer reviews
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
The roles of reliability and reputation in competitive multi agent systems
OTM'10 Proceedings of the 2010 international conference on On the move to meaningful internet systems - Volume Part I
Trust maximization in social networks
SBP'11 Proceedings of the 4th international conference on Social computing, behavioral-cultural modeling and prediction
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The recent emergence of location-based social networking services is revolutionizing web-based social networking allowing users to share real-life experiences via geo-tagged user-generated multimedia content. One of the key challenges of the web-based social networks as an information sharing and exchanging channel is how to manage healthy relationships among community users and ensure the quality of the information shared and exchanged within the community, which holds a very significant importance to user satisfaction. Deciding whom and what information to trust is very difficult in environment where the users are unknown to each other. This paper investigates the possibilities of managing trust between the users of a web-based social network while recommending items to the members of the network. A novel framework is proposed to integrate trust among community members and public reputation of items to recommend the most appropriate items to a user of the network.