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Heath, Tom; Motta, Enrico and Petre, Marian
(2007).
URL: http://www.eswc2007.org/workshops.php#swese
Abstract
Social networks can serve as both a rich source of new information and as a filter to identify the information most relevant to our specific needs. In this paper we present a methodology and algorithms that, by exploiting existing Semantic Web and Web2.0 data sources, help individuals identify who in their social network knows what, and who is the most trustworthy source of information on that topic. Our approach improves upon previous work in a number of ways, such as incorporating topic-specific rather than global trust metrics. This is achieved by generating topic experience profiles for each network member, based on data from Revyu and del.icio.us, to indicate who knows what. Identification of the most trustworthy sources is enabled by a rich trust model of information and recommendation seeking in social networks. Reviews and ratings created on Revyu provide source data for algorithms that generate topic expertise and person to person affinity metrics. Combining these metrics, we are implementing a user-oriented application for searching and automated ranking of information sources within social networks.
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About
- Item ORO ID
- 23610
- Item Type
- Conference or Workshop Item
- Extra Information
- Presented at Bridging the Gap between Semantic Web and Web 2.0, International Workshop located at 4th European Semantic Web Conference (ESWC 2007)
- Academic Unit or School
-
Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications - Research Group
- Centre for Research in Computing (CRC)
- Copyright Holders
- © The Authors
- Related URLs
- Depositing User
- Kay Dave