Please use this identifier to cite or link to this item: https://doi.org/10.1007/978-3-642-11301-7_56
DC FieldValue
dc.titleSensing geographical impact factor of multimedia news events for localized retrieval and news filtering
dc.contributor.authorZhang, X.
dc.contributor.authorLi, J.-T.
dc.contributor.authorZhang, Y.-D.
dc.contributor.authorNeo, S.-Y.
dc.date.accessioned2013-07-04T08:40:13Z
dc.date.available2013-07-04T08:40:13Z
dc.date.issued2009
dc.identifier.citationZhang, X.,Li, J.-T.,Zhang, Y.-D.,Neo, S.-Y. (2009). Sensing geographical impact factor of multimedia news events for localized retrieval and news filtering. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 5916 LNCS : 567-576. ScholarBank@NUS Repository. <a href="https://doi.org/10.1007/978-3-642-11301-7_56" target="_blank">https://doi.org/10.1007/978-3-642-11301-7_56</a>
dc.identifier.isbn3642113001
dc.identifier.issn03029743
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/41971
dc.description.abstractNews materials are reports on events occurring in a given time and location. Looking at the influence of individual event, an event that has news reported worldwide is strategically more important than one that is only covered by local news agencies. In fact, news coverage of an event can accurately determine the event's importance and potential impact on the society. In this paper, we present a framework which extracts the latent impact factor of events from multimedia news resources by a geographical approach to support: (a) localized retrieval for end users; and (b) pre-screening of potential news elements that should be filtered for use by web monitoring agencies. © 2010 Springer-Verlag Berlin Heidelberg.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1007/978-3-642-11301-7_56
dc.sourceScopus
dc.subjectFiltering
dc.subjectMultimedia News Impact Factor
dc.subjectRetrieval
dc.typeConference Paper
dc.contributor.departmentCOMPUTER SCIENCE
dc.description.doi10.1007/978-3-642-11301-7_56
dc.description.sourcetitleLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.description.volume5916 LNCS
dc.description.page567-576
dc.identifier.isiutNOT_IN_WOS
Appears in Collections:Staff Publications

Show simple item record
Files in This Item:
There are no files associated with this item.

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.