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Adaptive Multimedia Retrieval: Retrieval, User, and Semantics - 5th International Workshop, AMR 2007, Paris, France, July 5-6, 2007, Revised Selected Papers (Paperback, 2008 ed.)
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Adaptive Multimedia Retrieval: Retrieval, User, and Semantics - 5th International Workshop, AMR 2007, Paris, France, July 5-6, 2007, Revised Selected Papers (Paperback, 2008 ed.)
Series: Lecture Notes in Computer Science, 4918
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This bookis aselectionoftherevisedcontributionsthatwereinitially
submitted to the International Workshop on Adaptive Multimedia
Retrieval (AMR 2007). The workshop was organized at the University
Pierre and Marie Curie in Paris, France, during July 5-6, 2007. The
goalof the AMR workshopsis to intensify the exchangeof ideasbetween
di?erent research communities, to provide an overview of current
activities in this area and to point out connections between the
diverse involved researches communities, among them the most
important ones focussing on multimedia retrieval and arti?cial
intelligence. In this spirit, the ?rst three events where
collocated with Arti?cial Intelligence conferences: in 2003 as a
workshop of the 26th German Conference on Arti?cial Intelligence
(KI 2003); in 2004 as part of the 16th European Conference on
Arti?cial Intelligence (ECAI 2004) and in 2005 as part of the 19th
International Joint Conference on Arti?cial Intelligence
(IJCAI05).Becauseofitssuccess, in2006theUniversityofGeneva,
Switzerland, organized the workshop for the ?rst time as a
standalone event. In 2007 the workshop revealed three main topics:
retrieval, user and sem- tics.Retrieval, acoresubject,
wastackledfromseveralperspectives.Researchers were interested not
only in the e?ciency of the multimedia access by looking at
peer-to-peermethods, middlewareanddatabasestechniques,
butalsointhetype of retrieved data, ranging from music to images
and video. The user was also at the center of attention. Several
papers investigated the di?erent ways m- timedia data can be
searched, as, for instance, through navigation, summaries
andinteraction.Particularattentionwasgivento methods thattryto
modelthe user and its feedback. Finally, in this set of works, it
becomes clear that behind the idea of retrievaland user the notion
that connects both is hidden: sema
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