Adaptive Multimedia Retrieval: User, Context, and Feedback

Third International Workshop, AMR 2005, Glasgow, UK, July 28-29, 2005, Revised Selected Papers

Marcin Detyniecki, Joemon M. Jose, Andreas Nürnberger, C. J. Van Rijsbergen (Herausgeber)

Buch | Softcover

XII, 284 Seiten

2006
Springer Berlin (Verlag)
978-3-540-32174-3 (ISBN)

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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.

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.

Erscheint lt. Verlag	13.2.2006
Reihe/Serie	Information Systems and Applications, incl. Internet/Web, and HCI
Reihe/Serie	Lecture Notes in Computer Science
Zusatzinfo	XII, 284 p.
Verlagsort	Berlin
Sprache	englisch
Maße	155 x 235 mm
Gewicht	920 g
Themenwelt	Informatik ► Theorie / Studium ► Algorithmen
Schlagworte	Adaptive mulitmedia retrieval • Ambient Intelligence • Artificial Intelligence • Database • Distributed Systems • Extensible Markup Language (XML) • Image Retrieval • Intelligence • learning • machine learning • Mulitmedia information retrieval • Multimedia Databases • Retrieval Systems • Segmentation • semantic classifcation • spatio-temporal relations • Video Retrieval • Web Services
ISBN-10	3-540-32174-8 / 3540321748
ISBN-13	978-3-540-32174-3 / 9783540321743
Zustand	Neuware