Personalized News Video Recommendation


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LUO, Hangzai, Jianping FAN, Daniel A. KEIM, Shin ichi SATOH, 2008. Personalized News Video Recommendation. The 16th ACM international conference on Multimedia - MM '08. Vancouver, British Columbia, Canada, 26. Okt 2008 - 31. Okt 2008. In: Proceeding of the 16th ACM international conference on Multimedia - MM '08. New York, New York, USA:ACM Press, pp. 1001-1002. ISBN 978-1-60558-303-7. Available under: doi: 10.1145/1459359.1459549

@inproceedings{Luo2008Perso-5702, title={Personalized News Video Recommendation}, year={2008}, doi={10.1145/1459359.1459549}, isbn={978-1-60558-303-7}, address={New York, New York, USA}, publisher={ACM Press}, booktitle={Proceeding of the 16th ACM international conference on Multimedia - MM '08}, pages={1001--1002}, author={Luo, Hangzai and Fan, Jianping and Keim, Daniel A. and Satoh, Shin ichi} }

<rdf:RDF xmlns:dcterms="" xmlns:dc="" xmlns:rdf="" xmlns:bibo="" xmlns:dspace="" xmlns:foaf="" xmlns:void="" xmlns:xsd="" > <rdf:Description rdf:about=""> <dc:creator>Keim, Daniel A.</dc:creator> <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/> <dc:creator>Luo, Hangzai</dc:creator> <dspace:isPartOfCollection rdf:resource=""/> <dc:rights>terms-of-use</dc:rights> <dcterms:title>Personalized News Video Recommendation</dcterms:title> <dcterms:bibliographicCitation>Paper to be presented to: ACM International Conference on Multimedia 2009, Oct. 19-24, Beijing, China</dcterms:bibliographicCitation> <dc:creator>Fan, Jianping</dc:creator> <dcterms:issued>2008</dcterms:issued> <dc:contributor>Keim, Daniel A.</dc:contributor> <foaf:homepage rdf:resource="http://localhost:8080/jspui"/> <dc:contributor>Satoh, Shin ichi</dc:contributor> <dcterms:abstract xml:lang="eng">In this paper, a novel framework is developed to support personalized news video recommendation. First, multi-modal information sources for news videos are seamlessly integrated and synchronized to achieve more reliable news topic detection, and the contexts between different news topics are extracted automatically. Second, topic network and hyperbolic visualization are seamlessly integrated to support interactive navigation and exploration of large-scale collections of news videos at the topic level, so that users can gain deep insights of large-scale collections of news videos at the first glance. In such interactive topic network navigation and exploration process, users personal background knowledge can be exploited for selecting news topics of interest interactively, building up their mental models of news needs precisely and formulating their queries easily by selecting the visible news topics on the topic network directly. Our system can further recommend the relevant web news, the new search directions, and the most relevant news videos according to their importance and representativeness scores. Our experiments on large-scale collections of news videos have provided very positive results.</dcterms:abstract> <dspace:hasBitstream rdf:resource=""/> <dcterms:available rdf:datatype="">2011-03-24T15:59:28Z</dcterms:available> <dc:language>eng</dc:language> <dcterms:hasPart rdf:resource=""/> <dcterms:isPartOf rdf:resource=""/> <dc:date rdf:datatype="">2011-03-24T15:59:28Z</dc:date> <bibo:uri rdf:resource=""/> <dc:contributor>Fan, Jianping</dc:contributor> <dcterms:rights rdf:resource=""/> <dc:creator>Satoh, Shin ichi</dc:creator> <dc:format>application/pdf</dc:format> <dc:contributor>Luo, Hangzai</dc:contributor> </rdf:Description> </rdf:RDF>

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