By Thomas Sødring, Alan F. Smeaton (auth.), Fabio Crestani, Mark Girolami, Cornelis Joost van Rijsbergen (eds.)
The annual colloquium on info retrieval study presents a chance for either new and verified researchers to offer papers describing paintings in growth or ?nal effects. This colloquium used to be verified via the BCS IRSG(B- tish machine Society info Retrieval expert Group), and named the yearly Colloquium on details Retrieval study. lately, the site of the colloquium has alternated among the uk and continental Europe. To re?ect the becoming eu orientation of the development, the colloquium used to be renamed “European Annual Colloquium on details Retrieval study” from 2001. because the inception of the colloquium in 1979 the development has been hosted within the urban of Glasgow on 4 separate events. even though, this was once the ?rst time that the association of the colloquium have been together undertaken by means of 3 separate desktop and knowledge technological know-how 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 raise within the variety of pass- caliber submissions in solution to the decision for papers over prior years and as such fifty two submitted papers have been every one allotted three individuals 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 popularity fee of under forty five% and ensured a truly excessive average of the papers presented.
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Additional info for Advances in Information Retrieval: 24th BCS-IRSG European Colloquium on IR Research Glasgow, UK, March 25–27, 2002 Proceedings
J. ): ECIR 2002, LNCS 2291, pp. 41–52, 2002. c Springer-Verlag Berlin Heidelberg 2002 42 D. Heesch and S. R¨ uger The number of shape representations developed over the past ﬁfty years is bewildering. Each representation diﬀers in applicability and complexity. The simplest representations are based on so called “shape factors,” which are single values that capture but the minimal information of the object. These factors include, inter alia, the perimeter, the area, the radius, the elongation, the compactness, the number of corners, the circularity and the convexity of the object.
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 . IEEE Transactions on pattern analysis and machine intelligence, 22(12):1349–1379, 2000.
18. Reading notes by contour Table 4. 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.