Download Advances in Information Retrieval: 24th BCS-IRSG European by Thomas Sødring, Alan F. Smeaton (auth.), Fabio Crestani, PDF

By Thomas Sødring, Alan F. Smeaton (auth.), Fabio Crestani, Mark Girolami, Cornelis Joost van Rijsbergen (eds.)

The annual colloquium on details retrieval learn presents a chance for either new and proven researchers to give papers describing paintings in development or ?nal effects. This colloquium was once verified through the BCS IRSG(B- tish computing device Society info Retrieval professional Group), and named the once a year Colloquium on info Retrieval study. lately, the site of the colloquium has alternated among the uk and continental Europe. To re?ect the turning out to be ecu orientation of the development, the colloquium used to be renamed “European Annual Colloquium on info Retrieval learn” from 2001. because the inception of the colloquium in 1979 the development has been hosted within the urban of Glasgow on 4 separate events. despite the fact that, this used to be the ?rst time that the association of the colloquium have been together undertaken by way of 3 separate desktop and data technology departments; a sign of the collaborative nature and variety of IR learn in the universities of the West of Scotland. The organizers of ECIR 2002 observed a pointy elevate within the variety of cross- caliber submissions in resolution to the decision for papers over past years and as such fifty two submitted papers have been each one allotted three contributors of this system committee for double blind assessment of the manuscripts. a complete of 23 papers have been finally chosen for oral presentation on the colloquium in Glasgow which gave an attractiveness fee of below forty five% and ensured a truly excessive ordinary of the papers presented.

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Extra resources for Advances in Information Retrieval: 24th BCS-IRSG European Colloquium on IR Research Glasgow, UK, March 25–27, 2002 Proceedings

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18. G. J. McGill. Introduction to Modern Information Retrieval. McGraw-Hill, 1983. 19. S. Satoh, Y. Nakamura, and T. Kanade. Name-It: Naming and detecting faces in news videos. IEEE MultiMedia, 6(1):22–35, January-March 1999. 20. S. Sclaroff, M. La Cascia, S. Sethi, and L. Taycher. Unifying textual and visual cues for content-based image retrieval on the world wide web. Computer Vision and Image Understanding, 75(1–2):86–98, 1999. 21. A. Smeulders, M. Worring, S. Santini, A. Gupta, and R. Jain. Content-Based Image Retrieval at the End of the Early Years .

13. W. Niblack, R. Barber, W. Equitz, M. Flickner, E. Glasman, D. Petkovic, P. Yanker, C. Faloutsos, and G. Taubin. The QBIC project: querying images by content using color, texture and shape. In Wayne Niblack, editor, Storage and Retrieval for Image and Video Databases, pages 173–181, San Jose, CA, 1993. SPIE. 14. V. E. Ogle and M. Stonebraker. CHABOT: Retrieval from a relational database of images. IEEE Computer, 28(9):40–48, 1995. 15. W. P. Minka. Vision Texture for Annotation. Multimedia Systems, 3:3–14, 1995.

76 Number of notes files with perfect match 7,233 The fact that tables 3 and 4 are identical shows that no extra similarity benefits are to be gained by using note contour rather than exact note contour. 88% dissimilarity from the exact note contour experiment show that the extraction engine is good at extracting the correct note. This is confirmed by the fact that if the extraction engine was finding incorrect notes, these two dissimilarity figures would not be the same. Comparing tables 2 and 3 the dissimilarity figures differ by two orders of magnitude.

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