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Authors: Wendy Osborn and Marc Moreau

Affiliation: University of Lethbridge, Canada

ISBN: 978-989-758-096-3

Keyword(s): Spatial Access Methods, Very Large Object Sets, Performance.

Related Ontology Subjects/Areas/Topics: Data Engineering ; Databases and Data Security ; Databases and Information Systems Integration ; Enterprise Information Systems ; Large Scale Databases ; Non-Relational Databases ; Performance Evaluation and Benchmarking ; Query Languages and Query Processing

Abstract: This paper presents an evaluation of the mqr-tree for indexing a database containing a very large number of objects. Many spatial access methods have been proposed for handling either point and/or region data, with the vast majority able to handle a limited number of instances of these data types efficiently. However, many established and emerging application areas, such as recommender systems, require the management and indexing of very large object sets, such as a million places of interest that are each represented with a point. Using between one and five million points and objects, a comparison of both index construction and spatial query evaluation is performed versus a benchmark spatial indexing strategy. We show that the mqr-tree achieves significantly lower overlap and overcoverage when used to index a very large collection of objects. Also, the mqr-tree achieves significantly improved query processing performance in many cases. Therefore, the mqr-tree is a significant candida te for handling very large object sets for emerging applications. (More)

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Paper citation in several formats:
Osborn, W. and Moreau, M. (2015). The mqr-tree for Very Large Object Sets.In Proceedings of the 17th International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-096-3, pages 367-373. DOI: 10.5220/0005463203670373

@conference{iceis15,
author={Wendy Osborn. and Marc Moreau.},
title={The mqr-tree for Very Large Object Sets},
booktitle={Proceedings of the 17th International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2015},
pages={367-373},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005463203670373},
isbn={978-989-758-096-3},
}

TY - CONF

JO - Proceedings of the 17th International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - The mqr-tree for Very Large Object Sets
SN - 978-989-758-096-3
AU - Osborn, W.
AU - Moreau, M.
PY - 2015
SP - 367
EP - 373
DO - 10.5220/0005463203670373

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