A Quantitative Method for RSS Based Applications

Authors:
Mingwei Yuan;Ping Jiang;Jian Wu
Affiliations:
Department of Information and Control, Tongji University, China, email: yuan.mingwei@hotmail.com;Department of Information and Control, Tongji University, China, email: p.jiang@bradford.ac.uk and Department of Computing, University of Bradford, Bradford, BD7 1DP, UK.;Department of Information and Control, Tongji University, China, email: tongjiwujian@hotmail.com
Venue:
Proceedings of the 2008 conference on Applications of Data Mining in E-Business and Finance
Year:
2008

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Abstract

The RSS technique provides a fast and effective way to publish up-to-date information or renew outdated content for information subscribers. So far, RSS information is mostly managed by content publishers and Internet users have less initiative to choose what they really need. More attention needs to be paid on techniques for user-initiated information discovery from RSS feeds. In this paper, a quantitative semantic matchmaking method for RSS based applications is proposed. The semantic information of an RSS feed can be described by numerical vectors and semantic matching can then be conducted in a quantitative form. The ontology is applied to provide a common-agreed matching basis for the quantitative comparison. In order to avoid semantic ambiguity of literal statements from distributed RSS publishers, fuzzy inference is used to transform an individual-dependent vector into an individual-independent vector and semantic similarities can then be revealed as the result.