29,945 research outputs found
TopSig: Topology Preserving Document Signatures
Performance comparisons between File Signatures and Inverted Files for text
retrieval have previously shown several significant shortcomings of file
signatures relative to inverted files. The inverted file approach underpins
most state-of-the-art search engine algorithms, such as Language and
Probabilistic models. It has been widely accepted that traditional file
signatures are inferior alternatives to inverted files. This paper describes
TopSig, a new approach to the construction of file signatures. Many advances in
semantic hashing and dimensionality reduction have been made in recent times,
but these were not so far linked to general purpose, signature file based,
search engines. This paper introduces a different signature file approach that
builds upon and extends these recent advances. We are able to demonstrate
significant improvements in the performance of signature file based indexing
and retrieval, performance that is comparable to that of state of the art
inverted file based systems, including Language models and BM25. These findings
suggest that file signatures offer a viable alternative to inverted files in
suitable settings and from the theoretical perspective it positions the file
signatures model in the class of Vector Space retrieval models.Comment: 12 pages, 8 figures, CIKM 201
Challenging Ubiquitous Inverted Files
Stand-alone ranking systems based on highly optimized inverted file structures are generally considered ātheā solution for building search engines. Observing various developments in software and hardware, we argue however that IR research faces a complex engineering problem in the quest for more flexible yet efficient retrieval systems. We propose to base the development of retrieval systems on āthe database approachā: mapping high-level declarative specifications of the retrieval process into efficient query plans. We present the Mirror DBMS as a prototype implementation of a retrieval system based on this approach
Terrestrial applications: An intelligent Earth-sensing information system
For Abstract see A82-2214
Multi-view 3D retrieval using silhouette intersection and multi-scale contour representation
We describe in this paper two methods for 3D shape indexing
and retrieval that we apply on two data collections
of the SHREC - SHape Retrieval Contest 2007: Watertight
models and 3D CAD models. Both methods are based on a
set of 2D multi-views after a pose and scale normalization
of the models using PCA and the enclosing sphere. In all
views we extract the models silhouettes and compare them
pairwise. In the first method the similitude measure is obtained by integrating on the pairs of views the difference between the areas of the silhouettes union and the silhouettes intersection. In the second method we consider the external contour of the silhouettes, extract their convexities and concavities at different scale levels and build a multiscale representation. The pairs of contours are then compared by elastic matching achieved by using dynamic programming. Comparisons of the two methods are shown with their respective strengths and weaknesses
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