TY - CONF T1 - Rigorous Probabilistic Trust-Inference with Applications to Clustering T2 - IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technologies, 2009. WI-IAT '09 Y1 - 2009 A1 - DuBois,Thomas A1 - Golbeck,Jennifer A1 - Srinivasan, Aravind KW - Clustering algorithms KW - Conferences KW - Educational institutions KW - Extraterrestrial measurements KW - Inference algorithms KW - Intelligent agent KW - random graphs KW - Social network services KW - trust inferrence KW - Visualization KW - Voting KW - Web sites AB - The World Wide Web has transformed into an environment where users both produce and consume information. In order to judge the validity of information, it is important to know how trustworthy its creator is. Since no individual can have direct knowledge of more than a small fraction of information authors, methods for inferring trust are needed. We propose a new trust inference scheme based on the idea that a trust network can be viewed as a random graph, and a chain of trust as a path in that graph. In addition to having an intuitive interpretation, our algorithm has several advantages, noteworthy among which is the creation of an inferred trust-metric space where the shorter the distance between two people, the higher their trust. Metric spaces have rigorous algorithms for clustering, visualization, and related problems, any of which is directly applicable to our results. JA - IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technologies, 2009. WI-IAT '09 PB - IEEE VL - 1 SN - 978-0-7695-3801-3 M3 - 10.1109/WI-IAT.2009.109 ER -