In this paper we present RELEVANTNews, 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. RELEVANTNews 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.
RELEVANTNews: a Semantic News Feed Aggregator / S. Bergamaschi; F. Guerra; M. Orsini; C. Sartori; M. Vincini. - STAMPA. - 314:(2007), pp. 150-159. (Intervento presentato al convegno 4th Italian Semantic Web Workshop tenutosi a Bari, Italy nel 18-20 Dicembre 2007).
RELEVANTNews: a Semantic News Feed Aggregator
SARTORI, CLAUDIO;
2007
Abstract
In this paper we present RELEVANTNews, 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. RELEVANTNews 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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
