Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
The Journal of Machine Learning Research
The link prediction problem for social networks
CIKM '03 Proceedings of the twelfth international conference on Information and knowledge management
Evaluating collaborative filtering recommender systems
ACM Transactions on Information Systems (TOIS)
Propagation of trust and distrust
Proceedings of the 13th international conference on World Wide Web
Computing and applying trust in web-based social networks
Computing and applying trust in web-based social networks
The relationship between Precision-Recall and ROC curves
ICML '06 Proceedings of the 23rd international conference on Machine learning
Trust-aware recommender systems
Proceedings of the 2007 ACM conference on Recommender systems
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
Connections between the lines: augmenting social networks with text
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
TrustWalker: a random walk model for combining trust-based and item-based recommendation
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Controversial users demand local trust metrics: an experimental study on Epinions.com community
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 1
SUNNY: a new algorithm for trust inference in social networks using probabilistic confidence models
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
Predicting positive and negative links in online social networks
Proceedings of the 19th international conference on World wide web
Exploiting social context for review quality prediction
Proceedings of the 19th international conference on World wide web
Generating predictive movie recommendations from trust in social networks
iTrust'06 Proceedings of the 4th international conference on Trust Management
Getting one voice: tuning up experts' assessment in measuring accessibility
Proceedings of the International Cross-Disciplinary Conference on Web Accessibility
Integrating manual and automatic evaluations to measure accessibility barriers
ICCHP'12 Proceedings of the 13th international conference on Computers Helping People with Special Needs - Volume Part I
Enabling topic-level trust for collaborative information sharing
Personal and Ubiquitous Computing
Misleading opinions provided by advisors: dishonesty or subjectivity
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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In an online rating system, raters assign ratings to objects contributed by other users. In addition, raters can develop trust and distrust on object contributors depending on a few rating and trust related factors. Previous study has shown that ratings and trust links can influence each other but there has been a lack of a formal model to relate these factors together. In this paper, we therefore propose Trust Antecedent Factor (TAF) Model, a novel probabilistic model that generate ratings based on a number of rater's and contributor's factors. We demonstrate that parameters of the model can be learnt by Collapsed Gibbs Sampling. We then apply the model to predict trust and distrust between raters and review contributors using a real data-set. Our experiments have shown that the proposed model is capable of predicting both trust and distrust in a unified way. The model can also determine user factors which otherwise cannot be observed from the rating and trust data.