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Authors: Jens Emil Gydesen ; Henrik Haxholm ; Niels Sonnich Poulsen ; Sebastian Wahl and Bo Thiesson

Affiliation: Aalborg University, Denmark

ISBN: 978-989-758-076-5

Keyword(s): Data Mining, Indexing, Approximate Search, Multidimensional Data, Images, Data Representation.

Related Ontology Subjects/Areas/Topics: Applications ; Clustering ; Data Engineering ; Information Retrieval ; Ontologies and the Semantic Web ; Pattern Recognition ; Software Engineering ; Theory and Methods

Abstract: The increasing amount and size of data makes indexing and searching more difficult. It is especially challenging for multidimensional data such as images, videos, etc. In this paper we introduce a new indexable symbolic data representation that allows us to efficiently index and retrieve from a large amount of data that may appear in multiple dimensions. We use an approximate lower bounding distance measure to compute the distance between multidimensional arrays, which allows us to perform fast similarity searches. We present two search methods, exact and approximate, which can quickly retrieve data using our representation. Our approach is very general and works for many types of multidimensional data, including different types of image representations. Even for millions of multidimensional arrays, the approximate search will find a result in a few milliseconds, and will in many cases return a result similar to the best match.

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Paper citation in several formats:
Gydesen J., Haxholm H., Poulsen N., Wahl S. and Thiesson B. (2015). HyperSAX: Fast Approximate Search of Multidimensional Data.In Proceedings of the International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-076-5, pages 190-198. DOI: 10.5220/0005185201900198

@conference{icpram15,
author={Jens Emil Gydesen and Henrik Haxholm and Niels Sonnich Poulsen and Sebastian Wahl and Bo Thiesson},
title={HyperSAX: Fast Approximate Search of Multidimensional Data},
booktitle={Proceedings of the International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2015},
pages={190-198},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005185201900198},
isbn={978-989-758-076-5},
}

TY - CONF

JO - Proceedings of the International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - HyperSAX: Fast Approximate Search of Multidimensional Data
SN - 978-989-758-076-5
AU - Gydesen J.
AU - Haxholm H.
AU - Poulsen N.
AU - Wahl S.
AU - Thiesson B.
PY - 2015
SP - 190
EP - 198
DO - 10.5220/0005185201900198

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