Finding social network for trust calculation

Yutaka Matsuo, Hironori Tomobe, Kôiti Hasida, Mitsuru Ishizuka

Research output: Chapter in Book/Report/Conference proceedingConference contribution

24 Citations (Scopus)

Abstract

Trust is a necessary concept to realize the SemanticWeb. But how can we build a "Web of Trust"? We first argue that a small "Web of Trust" for each community is very essential to realize a huge "Web of Trust." Then, we focus on an academic community as a microcosm of a "Web of Trust" and show a web mining approach to generate a social network automatically. Each edge is added using the number of retrieved pages by a search engine which includes both persons' names. Moreover, each edge is given a label, such as "coauthors" or "members of the same project," by applying classification rules to the page content. The relation of persons such as "coauthor" or "same laboratory" can be described by an RDF format. Finally, using the social network, we calculate authoritativeness of a node as a social trust and an individual trust. National Institute of Advance Industrial Science and Technology (AIST), Japan email: y.matsuo@carc.aist.go.jp.

Original languageEnglish
Title of host publicationECAI 2004 - 16th European Conference on Artificial Intelligence, including Prestigious Applications of Intelligent Systems, PAIS 2004 - Proceedings
PublisherIOS Press
Pages510-514
Number of pages5
Volume110
ISBN (Electronic)9781586034528
Publication statusPublished - 2004
Externally publishedYes
Event16th European Conference on Artificial Intelligence, ECAI 2004 - Valencia, Spain
Duration: 2004 Aug 222004 Aug 27

Publication series

NameFrontiers in Artificial Intelligence and Applications
Volume110
ISSN (Print)09226389

Other

Other16th European Conference on Artificial Intelligence, ECAI 2004
Country/TerritorySpain
CityValencia
Period04/8/2204/8/27

ASJC Scopus subject areas

  • Artificial Intelligence

Fingerprint

Dive into the research topics of 'Finding social network for trust calculation'. Together they form a unique fingerprint.

Cite this