Services offered and provided through the Web have varying quality, and it is often difficult to assess the quality of a services before accessing and using it. Trust and reputation systems can be used in order to assist users in predicting and selecting the best quality services. This paper describes how Bayesian reputation systems can be combined with trust modeling based on subjective logic to provide an integrated method for assessing the quality of online services. This will not only assist the user's decision making, but will also provide an incentive for service providers to maintain high quality, and can be used as a sanctioning mechanism to discourage deceptive and low quality services.
|Name||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Conference||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Period||1/01/19 → …|