PNS: Personalized multi-source news delivery

Paliouras, G; Alexandros, M; Ntoutsis, C; Alexopoulos, A; Skourlas, C

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	https://dspace.lib.ntua.gr/xmlui/handle/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