Imagesemantics: User-Generated Metadata, Content Based Retrieval & Beyond

dc.creatorSpaniol,Marc
dc.creatorKlamma,Ralf
dc.creatorLux,Mathias
dc.date2008
dc.date.accessioned2024-02-06T12:56:38Z
dc.date.available2024-02-06T12:56:38Z
dc.descriptionWith the advent of Web 2.0 technologies a new attitude towards processing contents in the Internet has emerged. Nowadays it is a lot easier to create, share and retrieve multimedia contents on the Web. However, with the increasing amount in contents retrieval becomes more challenging and often leads to inadequate search results. One main reason is that image clustering and retrieval approaches usually stick either solely to the images' low-level features or their user-generated tags (high-level features). However, this is frequently inappropriate since the "real" semantics of an image can only be derived from the combination of low-level and high-level features. Consequently, we investigated a more holistic view on image semantics based on a system called Imagesemantics. This system combines MPEG-7 descriptions for low-level content-based retrieval features and MPEG-7 keywords by a machine learning approach producing joined OWL rules. The rule base is used in Imagesemantics to improve retrieval results.
dc.formattext/html
dc.identifierhttps://doi.org/10.3217/jucs-014-10-1792
dc.identifierhttps://lib.jucs.org/article/29091/
dc.identifier.urihttps://openrepository.mephi.ru/handle/123456789/9761
dc.languageen
dc.publisherJournal of Universal Computer Science
dc.relationinfo:eu-repo/semantics/altIdentifier/eissn/0948-6968
dc.relationinfo:eu-repo/semantics/altIdentifier/pissn/0948-695X
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rightsJ.UCS License
dc.sourceJUCS - Journal of Universal Computer Science 14(10): 1792-1807
dc.subjectWeb 2.0
dc.subjectsocial media platform
dc.subjectuser-generated content
dc.subjectMPEG-7
dc.titleImagesemantics: User-Generated Metadata, Content Based Retrieval & Beyond
dc.typeResearch Article
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