Adaptive Multimedia Retrieval: User, Context, and Feedback  Third International Workshop, AMR 2005, Glasgow, UK, July 28-29, 2005, Revised Selected Papers /  [electronic resource] : 
edited by Marcin Detyniecki, Joemon M. Jose, Andreas Nürnberger, C. J. van Rijsbergen. 
 - 1st ed. 2006. 
 - XII, 284 p.  online resource. 
 - Information Systems and Applications, incl. Internet/Web, and HCI,  3877  2946-1642 ; .
 - Information Systems and Applications, incl. Internet/Web, and HCI,  3877 .
<br/><br/>Invited Contributions -- Putting the User in the Loop: Visual Resource Discovery -- Using Relevance Feedback to Bridge the Semantic Gap -- Leveraging Context for Adaptive Multimedia Retrieval: A Matter of Control -- Ranking -- Rank-Ordering Documents According to Their Relevance in Information Retrieval Using Refinements of Ordered-Weighted Aggregations -- Ranking Invariance Based on Similarity Measures in Document Retrieval -- Systems -- Developing AMIE: An Adaptive Multimedia Integrated Environment -- Exploring the Structure of Media Stream Interactions for Multimedia Browsing -- CARSA - An Architecture for the Development of Context Adaptive Retrieval Systems -- Integrating Media Management Towards Ambient Intelligence -- CANDELA - Storage, Analysis and Retrieval of Video Content in Distributed Systems -- Spatio-temporal Relations -- Interactive Retrieval of Video Sequences from Local Feature Dynamics -- Temporal Relation Analysis in Audiovisual Documents for Complementary Descriptive Information -- Using Feedback -- Using Segmented Objects in Ostensive Video Shot Retrieval -- Learning User Queries in Multimodal Dissimilarity Spaces -- Surface Features in Video Retrieval -- Toward Consistent Evaluation of Relevance Feedback Approaches in Multimedia Retrieval -- Using Context -- An Explorative Study of Interface Support for Image Searching -- Context-Based Image Similarity Queries -- Meta Data -- Information Retrieval of Sequential Data in Heterogeneous XML Databases -- A Visual Annotation Framework Using Common-Sensical and Linguistic Relationships for Semantic Media Retrieval -- Improving Access to Multimedia Using Multi-source Hierarchical Meta-data. 
<br/><br/> This book is an extended collection of revised contributions that were initially submitted to the International Workshop on Adaptive Multimedia Retrieval (AMR 2005). This workshop was organized during July 28-29, 2005, at the U- versity of Glasgow, UK, as part of an information retrieval research festival and in co-location with the 19th International Joint Conference on Arti?cial Int- ligence (IJCAI 2005). AMR 2005 was the third and so far the biggest event of the series of workshops that started in 2003 with a workshop during the 26th German Conference on Arti?cial Intelligence (KI 2003) and continued in 2004 as part of the 16th European Conference on Arti?cial Intelligence (ECAI 2004). Theworkshopfocussedespeciallyonintelligentmethodstoanalyzeandstr- ture multimedia collections, with particular attention on methods that are able to support the user in the search process, e. g. , by providing additional user-and context-adapted information about the search results as well as the data coll- tion itself and especially by adapting the retrieval tool to the user's needs and interests. The invited contributions presented in the ?rst section of this book- "Putting the User in the Loop: Visual Resource Discovery" from Stefan Rug ¨ er, "Using Relevance Feedback to Bridge the Semantic Gap" from Ebroul Izquierdo and Divna Djordjevic, and "Leveraging Context for Adaptive Multimedia - trieval: A Matter of Control" from Gary Marchionini-illustrate these core t- ics: user,contextandfeedback. Theseaspectsarediscussedfromdi?erent points ofviewinthe18contributionsthatareclassi?edintosixmainchapters,following rather closely the workshop's sessions: ranking, systems, spatio-temporal re- tions, using feedback, using context and meta-data. 
<br/><br/><label>ISBN: </label>9783540321750 
<br/><br/><label>Standard No.: </label>10.1007/11670834  doi 
<br/><br/><label>Subjects--Topical Terms: </label><br/>Data structures (Computer science).<br/>Information theory.<br/>Information storage and retrieval systems.<br/>Multimedia systems.<br/>Application software.<br/>Computer vision.<br/>Artificial intelligence.<br/>Data Structures and Information Theory.<br/>Information Storage and Retrieval.<br/>Multimedia Information Systems.<br/>Computer and Information Systems Applications.<br/>Computer Vision.<br/>Artificial Intelligence.
<br/><br/><label>LC Class. No.: </label>QA76.9.D35 Q350-390 
<br/><br/><label>Dewey Class. No.: </label>005.73 003.54