Advances in Semantic Media Adaptation and Personalization, by Marios C. Angelides, Phivos Mylonas, Manolis Wallace

By Marios C. Angelides, Phivos Mylonas, Manolis Wallace

The emergence of content material- and context-aware se's, which not just customize looking and supply but in addition the content material, has triggered the emergence of recent infrastructures able to end-to-end ubiquitous transmission of custom-made multimedia content material to any machine on any community at any time. Personalizing and adapting content material calls for processing of content material and spotting styles in clients’ behaviour at the different. Personalizing and adapting the semantic content material of multimedia permits purposes to make just-in-time clever judgements relating to this content material, which in flip makes interplay with the multimedia content material someone and separately profitable event. Highlighting the altering nature of the sphere, Advances in Semantic Media edition and Personalization, quantity discusses the state-of-the-art, fresh advances, and destiny outlooks for semantic media version and personalization. subject matters contain: Collaborative content material Modeling automated content material function Extraction to content material versions Semantic Languages for content material Description Video content material variation Adaptive Video content material Retrieval content material Similarity Detection customized content material Podcasting Adaptive net interplay As content material and repair services realize the price of latest companies and new markets, they'll put money into applied sciences that adapt and customize content material. undefined, in reaction, has published new criteria akin to MPEG-7, MPEG21, and VC-1 that let propagation of semantic media, edition, and personalization. hence, a wide diversity of functions are rising throughout many sectors, corresponding to song, movie, video games, tv, and activities. Bringing jointly perception from researchers and practitioners, this e-book offers a sampling of the most recent considering within the box.

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The TemporalMask D, SpatialMask D, and SpatioTemporalMask D allow the boundaries a nd c omposition of t he segments to b e de scribed. Segments may be temporally connected to fo rm a c ontiguous segment over a tem poral interval, spatially connected to fo rm a c ontiguous spatial region, or spatiotemporally connected to fo rm a spat iotemporal segment that appears in a tem porally connected segment and is formed from spatially connected segments at each time instant. In addition, structural relation classification schemes allow relationships to be defined in time and space to provide relative references to content.

Finally, there is the challenge of community profiling. Members of virtual communities tend to share similar interests, experiences, expertise, and so forth, and thus b y g rouping u sers a ccording to t heir p rofiles, it i s p ossible to b ring si milar users together (Tang et al. 2008). These users are likely to have much richer interactions and are also likely to be content modeling on similar multimedia streams, thereby improving collaboration. Systems have been proposed for multimedia communities t hat enable c ollaboration of preferences a nd recommendations.

User p reference de scriptions en capsulated i n t he U serPreferences DS c an b e correlated w ith c ontent de scriptions a nd de scriptions o f u sers fo und w ithin t he AgentObjectDS and then aggregated across users to en able community profiling. Preferences are described by description tools such as the CreationPreferences DS, ClassificationPreferences DS, and SourcePreferences DS a nd can be used to i nfer user preferences for modeling content. The UsageHistory DS can further help with profiling by maintaining a record of user actions taken while modeling or viewing content.

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