The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
Authoritative sources in a hyperlinked environment
Proceedings of the ninth annual ACM-SIAM symposium on Discrete algorithms
The Eigentrust algorithm for reputation management in P2P networks
WWW '03 Proceedings of the 12th international conference on World Wide Web
TrustMe: Anonymous Management of Trust Relationships in Decentralized P2P Systems
P2P '03 Proceedings of the 3rd International Conference on Peer-to-Peer Computing
Link analysis ranking: algorithms, theory, and experiments
ACM Transactions on Internet Technology (TOIT)
A survey of trust in computer science and the Semantic Web
Web Semantics: Science, Services and Agents on the World Wide Web
Provenance and scientific workflows: challenges and opportunities
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Proceedings of the twenty-seventh ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Integrating conflicting data: the role of source dependence
Proceedings of the VLDB Endowment
Truth discovery and copying detection in a dynamic world
Proceedings of the VLDB Endowment
Global detection of complex copying relationships between sources
Proceedings of the VLDB Endowment
A Bayesian approach to discovering truth from conflicting sources for data integration
Proceedings of the VLDB Endowment
Truth finding on the deep web: is the problem solved?
Proceedings of the VLDB Endowment
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Many data management applications, such as setting up Web portals, managing enterprise data, managing community data, and sharing scientific data, require integrating data from multiple sources. Each of these sources provides a set of values and different sources can often provide conflicting values. To present quality data to users, it is critical to resolve conflicts and discover values that reflect the real world; this task is called data fusion. This paper describes a novel approach that finds true values from conflicting information when there are a large number of sources, among which some may copy from others. We present a case study on real-world data showing that the described algorithm can significantly improve accuracy of truth discovery and is scalable when there are a large number of data sources.