PNS: Personalized multi-source news delivery

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dc.contributor.author Paliouras, G en
dc.contributor.author Alexandros, M en
dc.contributor.author Ntoutsis, C en
dc.contributor.author Alexopoulos, A en
dc.contributor.author Skourlas, C en
dc.date.accessioned 2014-03-01T02:50:51Z
dc.date.available 2014-03-01T02:50:51Z
dc.date.issued 2006 en
dc.identifier.issn 03029743 en
dc.identifier.uri http://hdl.handle.net/123456789/35161
dc.relation.uri http://www.scopus.com/inward/record.url?eid=2-s2.0-33750692771&partnerID=40&md5=dc5e2d296875f32768f3ef7a8d6f0e8c en
dc.subject Information extraction en
dc.subject Machine learning en
dc.subject Personalization en
dc.subject.other Electronic data interchange en
dc.subject.other Learning systems en
dc.subject.other User interfaces en
dc.subject.other World Wide Web en
dc.subject.other Dynamic personalization en
dc.subject.other Information extraction en
dc.subject.other News delivery en
dc.subject.other Personalization en
dc.subject.other Information retrieval en
dc.title PNS: Personalized multi-source news delivery en
heal.type conferenceItem en
heal.publicationDate 2006 en
heal.abstract This paper presents a system that integrates news from multiple sources on the Web and delivers in a personalized fashion to the reader. The presented service integrates automatic information extraction from various news sources and presentation of information according to the user's interests. The system consists of source-specific information extraction programs (wrappers) that extract highlights of news items from the various sources, organize them according to pre-defined news categories and present them to the user through a personal Web-based interface. Dynamic personalization is used based on the user's reading history, as well as the preferences of other similar users. User models are maintained by statistical analysis and machine learning algorithms. Results of an initial user study have confirmed the value of the service and indicated ways in which it should be improved. © Springer-Verlag Berlin Heidelberg 2006. en
heal.journalName Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) en
dc.identifier.volume 4252 LNAI - II en
dc.identifier.spage 1152 en
dc.identifier.epage 1161 en

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