Trust network‐based filtering of aggregated claims
Source: International Journal of Metadata, Semantics and Ontologies, Volume 1, Number 1, 23 January 2006 , pp. 58-65(8)
Publisher: Inderscience Publishers
Abstract:On the semantic web, assertions may be aggregated from many sources, those aggregations filtered, reasoned over, aggregated with other aggregators, displayed, scraped, extracted, recombined, and otherwise processed without significant human oversight. To preserve the connection between assertions and their source, various provenance schemes for semantic web data have been explored. However, the primary focus has been on authenticating the author of a particular statement, e.g., using digital signatures, but there is no provision for relating the authenticity of the source of the assertion and the trustworthiness of the assertion itself. This paper presents a method for using semantic web based trust networks to infer the reputation of sources for a statement and compose the reputation of several sources. By calculating a trust rating for each statement based on the ratings of its sources, the set of statements can be filtered based on the rating.
Document Type: Research Article
Affiliations: 1: Maryland Information and Network Dynamics Laboratory, University of Maryland, College Park, MD 20742, USA. 2: Maryland Information and Network Dynamics Laboratory, University of Maryland, College Park, MD 20742, USA
Publication date: January 23, 2006
- International Journal of Metadata, Semantics and Ontologies aims at publishing research advances and discussions about meta-data in a broad sense, and about their associated semantics and ontological structures, from a multi-disciplinary perspective, and with an emphasis on domain-specific ontologies and organisational, human interaction and social issues regarding metadata annotation, use and assessment. It also intends covering Semantic Web research, as a concrete metadata-intensive technological framework in which shared and standardised semantics are a critical issue.
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