RELEVANTNews: a Semantic News Feed Aggregator.
Sonia Bergamaschi, Francesco Guerra, Mirko Orsini, Claudio Sartori, Maurizio Vincini · IRIS UNIMORE (University of Modena and Reggio Emilia) · 2007
Abstract. In this paper we present RELEVANT News, a web feed reader that automatically groups news related to the same topic published in different newspapers in different days. The tool is based on RELEVANT, a previously developed tool, which computes the “relevant values”, i.e. a subset of the values of a string attribute. Clustering the titles of the news feeds selected by the user, it is possible identify sets of related news on the basis of syntactic and lexical similarity. RELEVANT News may be used in its default configuration or in a personalized way: the user may tune some parameters in order to improve the grouping results. We tested the tool with more than 700 news published in 30 newspapers in four days and some preliminary results are discussed. 1