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 .

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.

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.

9783540321750

10.1007/11670834 doi


Data structures (Computer science).
Information theory.
Information storage and retrieval systems.
Multimedia systems.
Application software.
Computer vision.
Artificial intelligence.
Data Structures and Information Theory.
Information Storage and Retrieval.
Multimedia Information Systems.
Computer and Information Systems Applications.
Computer Vision.
Artificial Intelligence.

QA76.9.D35 Q350-390

005.73 003.54