Carol Peters

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 - Information Systems and Applications Carol Peters

Marc Notes: Includes bibliographical references and index.; Electronic reproduction.; Palo Alto, Calif.: ebrary; 2010.; Available via World Wide Web.; Access may be limited to ebrary affiliated libraries. Table of Contents: 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.- Analysis Combination and Pseudo Relevance Feedback in Conceptual Language Model.- The MedGIFT Group at ImageCLEF2009.- 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 Jaen 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 Content Enrichment.- 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."