Semantic-based Merging of RSS Items

Authors:
Fekade Getahun Taddesse;Joe Tekli;Richard Chbeir;Marco Viviani;Kokou Yetongnon
Affiliations:
LE2I Laboratory UMR-CNRS, University of Bourgogne, Dijon Cedex, France 21078;LE2I Laboratory UMR-CNRS, University of Bourgogne, Dijon Cedex, France 21078;LE2I Laboratory UMR-CNRS, University of Bourgogne, Dijon Cedex, France 21078;LE2I Laboratory UMR-CNRS, University of Bourgogne, Dijon Cedex, France 21078;LE2I Laboratory UMR-CNRS, University of Bourgogne, Dijon Cedex, France 21078
Venue:
World Wide Web
Year:
2010

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Abstract

Merging XML documents can be of key importance in several applications. For instance, merging the RSS news from same or different sources and providers can be beneficial for end-users in various scenarios. In this paper, we address this issue and explore the relatedness measure between RSS elements. We show here how to define and compute exclusive relations between any two elements and provide several predefined merging operators that can be extended and adapted to human needs. We also provide a set of experiments conducted to validate our approach.