By Thomas Sødring, Alan F. Smeaton (auth.), Fabio Crestani, Mark Girolami, Cornelis Joost van Rijsbergen (eds.)
The annual colloquium on details retrieval learn offers a chance for either new and tested researchers to give papers describing paintings in growth or ?nal effects. This colloquium was once verified by means of the BCS IRSG(B- tish machine Society info Retrieval professional Group), and named the once a year Colloquium on details Retrieval learn. 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 was once renamed “European Annual Colloquium on info Retrieval examine” from 2001. because the inception of the colloquium in 1979 the development has been hosted within the urban of Glasgow on 4 separate events. although, this was once the ?rst time that the association of the colloquium were together undertaken via 3 separate desktop and data 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 move- caliber submissions in resolution 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 attractiveness cost of under forty five% and ensured a really excessive typical of the papers presented.
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Additional resources for Advances in Information Retrieval: 24th BCS-IRSG European Colloquium on IR Research Glasgow, UK, March 25–27, 2002 Proceedings
Moment invariants. Moments capture distributional properties of a random variable. The ﬁrst moment is equivalent to the expected value, while the second central moment yields the variance of that variable. For 2-d black-and-white images of size N · M , nth order moments are deﬁned as N ·M Mpq = i=1 xpi yiq f (xi , yi ), where p, q ∈ N with p + q = n and f (xi , yi ) = 1 if the pixel i at position (xi , yi ) is set and 0 otherwise. Translation invariance can be achieved by central moments N ·M Cpq = (xi − x ¯)p (yi − y¯)q f (xi , yi ), i=1 where x ¯ = M10 /M00 and y¯ = M01 /M00 .
In our approach, agglomerative hierarchical clustering (AHC) has been chosen to classify the corpus. Other works suggested alternative classiﬁcations of images based on visual features . 2 above; the resulting structure is called “dendrogram”. The textual dendrogram includes only textually indexed images, that is, potentially few images. The visual dendrogram, however, includes all images, as the colour feature computation can be carried out automatically. The advantage of hierarchical structure is that the cluster size can be controlled by a cut-oﬀ value (cf.
Maybury, editor, Intelligent Multimedia Information Retrieval, pages 23–41. AAAI Press, Menlo Park, 1997. 23. J. H. Ballard. Color indexing. International Journal of Computer Vision, 7(1):11–32, 1991. 24. E. Voorhees. The Eﬀectiveness and Eﬃciency of Agglomerative Hierarchic Clustering in Document Retrieval. PhD thesis, Cornell University, Ithaca, NY, Etats-Unis, 1985. Rapport Technique TR 85-705. 25. T. S. Lee, and F. Safayeni. The Retrieval of Images from Image Databases. Behaviour & Information Technology, 14(1):3–13, 1995.