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https://hdl.handle.net/20.500.14279/3557
Τίτλος: | Unsupervised clustering of clickthrough data for automatic annotation of multimedia content | Συγγραφείς: | Tsapatsoulis, Nicolas Ntalianis, Klimis S. Doulamis, Anastasios D. |
metadata.dc.contributor.other: | Τσαπατσούλης, Νικόλας | Major Field of Science: | Social Sciences | Field Category: | Media and Communications | Λέξεις-κλειδιά: | Computer science;Neural networks;Multimedia systems;Search engines;Cluster analysis;Back propagation (Artificial intelligence) | Ημερομηνία Έκδοσης: | 2009 | Πηγή: | Artificial neural networks – ICANN 2009: 19th International Conference, Limassol, Cyprus, September 14-17, 2009, Proceedings, Part II, Pages 895-904 | Περίληψη: | Current low-level feature-based CBIR methods do not provide meaningful results on non-annotated content. On the other hand manual annotation is both time/money consuming and user-dependent. To address these problems in this paper we present an automatic annotation approach by clustering, in an unsupervised way, clickthrough data of search engines. In particular the query-log and the log of links the users clicked on are analyzed in order to extract and assign keywords to selected content. Content annotation is also accelerated by a carousel-like methodology. The proposed approach is feasible even for large sets of queries and features and theoretical results are verified in a controlled experiment, which shows that the method can effectively annotate multimedia files | URI: | https://hdl.handle.net/20.500.14279/3557 | ISBN: | 978-3-642-04276-8 (print) | ISSN: | 978-3-642-04277-5 (online) | DOI: | 10.1007/978-3-642-04277-5_90 | Rights: | © Springer Berlin Heidelberg | Type: | Book Chapter | Affiliation: | National Technical University Of Athens Technical University of Crete Cyprus University of Technology |
Εμφανίζεται στις συλλογές: | Κεφάλαια βιβλίων/Book chapters |
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