Information filtering based on user behavior analysis and best match text retrieval
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
REGRET: reputation in gregarious societies
Proceedings of the fifth international conference on Autonomous agents
An algorithm for automated rating of reviewers
Proceedings of the 1st ACM/IEEE-CS joint conference on Digital libraries
Computing and using reputations for internet ratings
Proceedings of the 3rd ACM conference on Electronic Commerce
An evidential model of distributed reputation management
Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 1
Reputation and social network analysis in multi-agent systems
Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 1
Consumer trust in an Internet store
Information Technology and Management
Scoring the Data Using Association Rules
Applied Intelligence
The Eigentrust algorithm for reputation management in P2P networks
WWW '03 Proceedings of the 12th international conference on World Wide Web
Propagation of trust and distrust
Proceedings of the 13th international conference on World Wide Web
Simplification and analysis of transitive trust networks
Web Intelligence and Agent Systems
A survey of trust in computer science and the Semantic Web
Web Semantics: Science, Services and Agents on the World Wide Web
Trust network-based filtering of aggregated claims
International Journal of Metadata, Semantics and Ontologies
Predicting trusts among users of online communities: an epinions case study
Proceedings of the 9th ACM conference on Electronic commerce
Key figure impact in trust-enhanced recommender systems
AI Communications - Recommender Systems
International Journal of Electronic Commerce
In Justice We Trust: Predicting User Acceptance of E-Customer Services
Journal of Management Information Systems
Fuzzy computational models for trust and reputation systems
Electronic Commerce Research and Applications
The slashdot zoo: mining a social network with negative edges
Proceedings of the 18th international conference on World wide web
Community gravity: measuring bidirectional effects by trust and rating on online social networks
Proceedings of the 18th international conference on World wide web
The SocialTrust framework for trusted social information management: Architecture and algorithms
Information Sciences: an International Journal
Improved trust-aware recommender system using small-worldness of trust networks
Knowledge-Based Systems
Novel personal and group-based trust models in collaborative filtering for document recommendation
Information Sciences: an International Journal
Exploiting two-faceted web of trust for enhanced-quality recommendations
Expert Systems with Applications: An International Journal
Generating trusted graphs for trust evaluation in online social networks
Future Generation Computer Systems
Trust models and applications in communication and multi-agent systems
International Journal of Knowledge-based and Intelligent Engineering Systems - Selected papers of KES2012-Part 2 of 2
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As online experience sharing sites have become one of the popular collaborative online communities, people are easily able to share their good and bad experiences on various products and services with a large number of unknown people as well as their friends. These experience sharing communities try to encourage social interaction among people and facilitate experience sharing and dissemination with satisfaction. The social interactions among users in such online communities are constructed based on trust that is established from each user's subjective perspective on the experiences in the community. Since a robust trust system is vital in experience sharing online communities, we therefore propose a computational trust framework for predicting a degree of trust or trust-connection between a pair of users. The Web of Trust, which consists of explicit trust rating among users, is not always available and is typically sparse, so the proposed framework does not rely on a Web of Trust. The proposed trust system measures a degree of trust based on users' expertise and preferences regarding topics (i.e. categories), using users feedback rating data which are available and much denser than a Web of Trust. In order to derive a more personalized degree of trust, the expertise- and preference-based trust is refined with each user's subjective and direct experiences with community members as well as a target user. The empirical experiments show that our proposed trust framework is quite promising in ratings-based online experience sharing communities, even when there are not enough user feedback ratings to predict a degree of trust.