Multilingual Information Access Evaluation II - Multimedia Experiments 10th Workshop of the Cross-Language Evaluation Forum, CLEF 2009, Corfu, Greece, September 30 - October 2, 2009, Revised Selected Papers, Part II / [electronic resource] : edited by Carol Peters, Barbara Caputo, Julio Gonzalo, Gareth Jones, Jayashree Kalpathy-Cramer, Henning Müller, Theodora Tsikrika. - 1st ed. 2010. - XXV, 678 p. 80 illus. online resource. - Information Systems and Applications, incl. Internet/Web, and HCI, 6242 2946-1642 ; . - Information Systems and Applications, incl. Internet/Web, and HCI, 6242 .

What Happened in CLEF 2009 -- What Happened in CLEF 2009 -- I: Interactive Cross-Language Retrieval (iCLEF) -- Overview of iCLEF 2009: Exploring Search Behaviour in a Multilingual Folksonomy Environment -- Analysis of Multilingual Image Search Logs: Users' Behavior and Search Strategies -- User Behaviour and Lexical Ambiguity in Cross-Language Image Retrieval -- Users' Image Seeking Behavior in a Multilingual Tag Environment -- II: Cross-Language Retrieval in Image Collections (ImageCLEF) -- Diversity in Photo Retrieval: Overview of the ImageCLEFPhoto Task 2009 -- Overview of the WikipediaMM Task at ImageCLEF 2009 -- Overview of the CLEF 2009 Medical Image Retrieval Track -- Overview of the CLEF 2009 Medical Image Annotation Track -- Overview of the CLEF 2009 Large-Scale Visual Concept Detection and Annotation Task -- Overview of the CLEF 2009 Robot Vision Track -- ImageCLEFPhoto -- Diversity Promotion: Is Reordering Top-Ranked Documents Sufficient? -- Comparison of Several Combinations of Multimodal and Diversity Seeking Methods for Multimedia Retrieval -- University of Glasgow at ImageCLEFPhoto 2009: Optimising Similarity and Diversity in Image Retrieval -- Multimedia Retrieval by Means of Merge of Results from Textual and Content Based Retrieval Subsystems -- Image Query Expansion Using Semantic Selectional Restrictions -- Clustering for Text and Image-Based Photo Retrieval at CLEF 2009 -- ImageCLEFwiki -- Combining Text/Image in WikipediaMM Task 2009 -- Document Expansion for Text-Based Image Retrieval at CLEF 2009 -- Multimodal Image Retrieval over a Large Database -- Using WordNet in Multimedia Information Retrieval -- ImageCLEFmed -- Medical Image Retrieval: ISSR at CLEF 2009 -- An Integrated Approach for Medical Image Retrieval through Combining Textual and Visual Features -- AnalysisCombination and Pseudo Relevance Feedback in Conceptual Language Model -- The MedGIFT Group at ImageCLEF 2009 -- An Extended Vector Space Model for Content Based Image Retrieval -- Using Media Fusion and Domain Dimensions to Improve Precision in Medical Image Retrieval -- ImageCLEFmed Annotation -- ImageCLEF 2009 Medical Image Annotation Task: PCTs for Hierarchical Multi-Label Classification -- Dense Simple Features for Fast and Accurate Medical X-Ray Annotation -- Automated X-Ray Image Annotation -- ImageCLEF Annotation and Robot Vision -- Topological Localization of Mobile Robots Using Probabilistic Support Vector Classification -- The University of Amsterdam's Concept Detection System at ImageCLEF 2009 -- Enhancing Recognition of Visual Concepts with Primitive Color Histograms via Non-sparse Multiple Kernel Learning -- Using SIFT Method for Global Topological Localization for Indoor Environments -- UAIC at ImageCLEF 2009 Photo Annotation Task -- Learning Global and Regional Features for Photo Annotation -- Improving Image Annotation in Imbalanced Classification Problems with Ranking SVM -- University of Glasgow at ImageCLEF 2009 Robot Vision Task: A Rule Based Approach -- A Fast Visual Word Frequency - Inverse Image Frequency for Detector of Rare Concepts -- Exploring the Semantics behind a Collection to Improve Automated Image Annotation -- Multi-cue Discriminative Place Recognition -- MRIM-LIG at ImageCLEF 2009: Robotvision, Image Annotation and Retrieval Tasks -- ImageCLEF Mixed -- The ImageCLEF Management System -- Interest Point and Segmentation-Based Photo Annotation -- University of Jaén at ImageCLEF 2009: Medical and Photo Tasks -- III: Cross-Language Retrieval in Video Collections (VideoCLEF) -- Overview of VideoCLEF 2009: New Perspectives on Speech-Based Multimedia ContentEnrichment -- Methods for Classifying Videos by Subject and Detecting Narrative Peak Points -- Using Support Vector Machines as Learning Algorithm for Video Categorization -- Video Classification as IR Task: Experiments and Observations -- Exploiting Speech Recognition Transcripts for Narrative Peak Detection in Short-Form Documentaries -- Identification of Narrative Peaks in Video Clips: Text Features Perform Best -- A Cocktail Approach to the VideoCLEF'09 Linking Task -- When to Cross Over? Cross-Language Linking Using Wikipedia for VideoCLEF 2009.

The tenth campaign of the Cross Language Evaluation Forum (CLEF) for European languages was held from January to September 2009. There were eight main eval- tion tracks in CLEF 2009 plus a pilot task. The aim, as usual, was to test the perfo- ance of a wide range of multilingual information access (MLIA) systems or system components. This year, about 150 groups, mainly but not only from academia, reg- tered to participate in the campaign. Most of the groups were from Europe but there was also a good contingent from North America and Asia. The results were presented at a two-and-a-half day workshop held in Corfu, Greece, September 30 to October 2, 2009, in conjunction with the European Conference on Digital Libraries. The workshop, attended by 160 researchers and system developers, provided the opportunity for all the groups that had participated in the evaluation campaign to get together, compare approaches and exchange ideas.

9783642157516

10.1007/978-3-642-15751-6 doi


Natural language processing (Computer science).
Application software.
Information storage and retrieval systems.
Database management.
Data mining.
Pattern recognition systems.
Natural Language Processing (NLP).
Computer and Information Systems Applications.
Information Storage and Retrieval.
Database Management.
Data Mining and Knowledge Discovery.
Automated Pattern Recognition.

QA76.9.N38

006.35