NDLI: Combining Approximation Techniques and Vector Quantization for Adaptable Similarity Search

Content Provider	Springer Nature Link
Author	Böhm, Christian Kriegel, Hans Peter Seidl, Thomas
Copyright Year	2002
Abstract	Adaptable similarity queries based on quadratic form distance functions are widely popular in data mining application domains including multimedia, CAD, molecular biology or medical image databases. Recently it has been recognized that quantization of feature vectors can substantially improve query processing for Euclidean distance functions, as demonstrated by the scan-based VA-file and the index structure IQ-tree. In this paper, we address the problem that determining quadratic form distances between quantized vectors is difficult and computationally expensive. Our solution provides a variety of new approximation techniques for quantized vectors which are combined by an extended multistep query processing architecture. In our analysis section, we show that the filter steps complement each other. Consequently, it is useful to apply our filters in combination. We show the superiority of our approach over other architectures and over competitive query processing methods. In our experimental evaluation, the sequential scan is outperformed by a factor of 2.3. Compared to the X-tree on 64 dimensional color histogram data, we measured an improvement factor of 5.7.
Starting Page	207
Ending Page	230
Page Count	24
File Format	PDF
ISSN	09259902
Journal	Journal of Intelligent Information Systems
Volume Number	19
Issue Number	2
e-ISSN	15737675
Language	English
Publisher	Kluwer Academic Publishers
Publisher Date	2002-01-01
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Data Structures, Cryptology and Information Theory Artificial Intelligence (incl. Robotics) Document Preparation and Text Processing Business Information Systems
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Computer Networks and Communications Information Systems Software Hardware and Architecture

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