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

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

ISBN-10: 3540433430

ISBN-13: 9783540433439

ISBN-10: 3540458867

ISBN-13: 9783540458869

The annual colloquium on details retrieval examine presents a chance for either new and demonstrated researchers to provide papers describing paintings in development or ?nal effects. This colloquium used to be confirmed via the BCS IRSG(B- tish computing device Society details Retrieval professional Group), and named the yearly 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. notwithstanding, this used to be the ?rst time that the association of the colloquium were together undertaken by means of 3 separate laptop and data technological know-how departments; a sign of the collaborative nature and variety of IR examine 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 past years and as such fifty two submitted papers have been every one allotted three individuals of this system committee for double blind evaluation of the manuscripts. a complete of 23 papers have been ultimately chosen for oral presentation on the colloquium in Glasgow which gave an popularity fee of under forty five% and ensured a truly excessive ordinary 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

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We are dealing with complex images, that would require more accurate features. As a consequence, texture and shape features ought to be incorporated in an efficient visual similarity measure. This yields, however, to additional problems. Texture feature is only relevant for a small, homogeneous image clip: if various textures are present in this clip, then the texture feature will capture a “blurred” vision of this sub-image. When it comes to shape description, the difficult problem of shape identification arises.

The cluster size grows as we consider higher levels, and this suggests a simple way to balance precision against recall (Precision is defined as the proportion of the retrieved documents which are relevant, whereas recall is the proportion of relevant documents that are actually retrieved). The cut-off value is determined during retrieval session, and is thus context-adaptive. A cut−off value A B C C1 D C2 E F C3 Fig. 1. The dendrogram: a hierarchic structure produced by Agglomerative Hierarchic Clustering.

3 25 Classification-Based Corpus Organisation For corpus organisation purposes we focused on clustering techniques [3], which aim at grouping similar objects. These techniques have been extensively used and studied in the field of Information Retrieval [8,24,5,26]. It is also worth noting that these techniques have been mainly applied to textual information organisation; we intend to use them for image classification as well, based on visual features. In our approach, agglomerative hierarchical clustering (AHC) has been chosen to classify the corpus.

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Advances in Information Retrieval: 24th BCS-IRSG European Colloquium on IR Research Glasgow, UK, March 25–27, 2002 Proceedings by Thomas Sødring, Alan F. Smeaton (auth.), Fabio Crestani, Mark Girolami, Cornelis Joost van Rijsbergen (eds.)

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