Object Fusion in Geographic Information Systems

Catriel Beeri; Yaron Kanza; Eliyahu Safra; Yehoshua Sagiv

doi:10.1016/b978-012088469-8.50072-3

Object Fusion in Geographic Information Systems

Catriel Beeri
, Yaron Kanza
, Eliyahu Safra
, Yehoshua Sagiv

The Rachel and Selim Benin School of Engineering and Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

Given two geographic databases, a fusion algorithm should produce all pairs of corresponding objects (i.e., objects that represent the same real-world entity). Four fusion algorithms, which only use locations of objects, are described and their performance is measured in terms of recall and precision. These algorithms are designed to work even when locations are imprecise and each database represents only some of the real-world entities. Results of extensive experimentation are presented and discussed. The tests show that the performance depends on the density of the data sources and the degree of overlap among them. All four algorithms are much better than the current state of the art (i.e., the one-sided nearest-neighbor join). One of these four algorithms is best in all cases, at a cost of a small increase in the running time compared to the other algorithms.

Original language	English
Title of host publication	VLDB 2004 - Proceedings of the 30th International Conference on Very Large Data Bases
Editors	Mario A. Nascimento, M. Tamer Ozsu, Donald Kossmann, Renee J. Miller, Jose A. Blakeley, K. Bernhard Schiefer
Publisher	Morgan Kaufmann Publishers, Inc.
Pages	816-827
Number of pages	12
ISBN (Electronic)	0120884690, 9780120884698
DOIs	https://doi.org/10.1016/b978-012088469-8.50072-3
State	Published - 2004
Event	30th International Conference on Very Large Data Bases, VLDB 2004 - Toronto, Canada Duration: 31 Aug 2004 → 3 Sep 2004

Publication series

Name	VLDB 2004 - Proceedings of the 30th International Conference on Very Large Data Bases

Conference

Conference	30th International Conference on Very Large Data Bases, VLDB 2004
Country/Territory	Canada
City	Toronto
Period	31/08/04 → 3/09/04

Bibliographical note

Publisher Copyright:
© VLDB 2004 - Proceedings of the 30th International Conference on Very Large Data Bases.

Access to Document

10.1016/b978-012088469-8.50072-3

Cite this

Beeri, C., Kanza, Y., Safra, E., & Sagiv, Y. (2004). Object Fusion in Geographic Information Systems. In M. A. Nascimento, M. T. Ozsu, D. Kossmann, R. J. Miller, J. A. Blakeley, & K. B. Schiefer (Eds.), VLDB 2004 - Proceedings of the 30th International Conference on Very Large Data Bases (pp. 816-827). (VLDB 2004 - Proceedings of the 30th International Conference on Very Large Data Bases). Morgan Kaufmann Publishers, Inc.. https://doi.org/10.1016/b978-012088469-8.50072-3

Beeri, Catriel ; Kanza, Yaron ; Safra, Eliyahu et al. / Object Fusion in Geographic Information Systems. VLDB 2004 - Proceedings of the 30th International Conference on Very Large Data Bases. editor / Mario A. Nascimento ; M. Tamer Ozsu ; Donald Kossmann ; Renee J. Miller ; Jose A. Blakeley ; K. Bernhard Schiefer. Morgan Kaufmann Publishers, Inc., 2004. pp. 816-827 (VLDB 2004 - Proceedings of the 30th International Conference on Very Large Data Bases).

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title = "Object Fusion in Geographic Information Systems",

abstract = "Given two geographic databases, a fusion algorithm should produce all pairs of corresponding objects (i.e., objects that represent the same real-world entity). Four fusion algorithms, which only use locations of objects, are described and their performance is measured in terms of recall and precision. These algorithms are designed to work even when locations are imprecise and each database represents only some of the real-world entities. Results of extensive experimentation are presented and discussed. The tests show that the performance depends on the density of the data sources and the degree of overlap among them. All four algorithms are much better than the current state of the art (i.e., the one-sided nearest-neighbor join). One of these four algorithms is best in all cases, at a cost of a small increase in the running time compared to the other algorithms.",

author = "Catriel Beeri and Yaron Kanza and Eliyahu Safra and Yehoshua Sagiv",

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doi = "10.1016/b978-012088469-8.50072-3",

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Beeri, C, Kanza, Y, Safra, E & Sagiv, Y 2004, Object Fusion in Geographic Information Systems. in MA Nascimento, MT Ozsu, D Kossmann, RJ Miller, JA Blakeley & KB Schiefer (eds), VLDB 2004 - Proceedings of the 30th International Conference on Very Large Data Bases. VLDB 2004 - Proceedings of the 30th International Conference on Very Large Data Bases, Morgan Kaufmann Publishers, Inc., pp. 816-827, 30th International Conference on Very Large Data Bases, VLDB 2004, Toronto, Canada, 31/08/04. https://doi.org/10.1016/b978-012088469-8.50072-3

Object Fusion in Geographic Information Systems. / Beeri, Catriel; Kanza, Yaron; Safra, Eliyahu et al.
VLDB 2004 - Proceedings of the 30th International Conference on Very Large Data Bases. ed. / Mario A. Nascimento; M. Tamer Ozsu; Donald Kossmann; Renee J. Miller; Jose A. Blakeley; K. Bernhard Schiefer. Morgan Kaufmann Publishers, Inc., 2004. p. 816-827 (VLDB 2004 - Proceedings of the 30th International Conference on Very Large Data Bases).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Beeri, Catriel

AU - Kanza, Yaron

AU - Safra, Eliyahu

AU - Sagiv, Yehoshua

N1 - Publisher Copyright: © VLDB 2004 - Proceedings of the 30th International Conference on Very Large Data Bases.

PY - 2004

Y1 - 2004

N2 - Given two geographic databases, a fusion algorithm should produce all pairs of corresponding objects (i.e., objects that represent the same real-world entity). Four fusion algorithms, which only use locations of objects, are described and their performance is measured in terms of recall and precision. These algorithms are designed to work even when locations are imprecise and each database represents only some of the real-world entities. Results of extensive experimentation are presented and discussed. The tests show that the performance depends on the density of the data sources and the degree of overlap among them. All four algorithms are much better than the current state of the art (i.e., the one-sided nearest-neighbor join). One of these four algorithms is best in all cases, at a cost of a small increase in the running time compared to the other algorithms.

AB - Given two geographic databases, a fusion algorithm should produce all pairs of corresponding objects (i.e., objects that represent the same real-world entity). Four fusion algorithms, which only use locations of objects, are described and their performance is measured in terms of recall and precision. These algorithms are designed to work even when locations are imprecise and each database represents only some of the real-world entities. Results of extensive experimentation are presented and discussed. The tests show that the performance depends on the density of the data sources and the degree of overlap among them. All four algorithms are much better than the current state of the art (i.e., the one-sided nearest-neighbor join). One of these four algorithms is best in all cases, at a cost of a small increase in the running time compared to the other algorithms.

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Beeri C, Kanza Y, Safra E, Sagiv Y. Object Fusion in Geographic Information Systems. In Nascimento MA, Ozsu MT, Kossmann D, Miller RJ, Blakeley JA, Schiefer KB, editors, VLDB 2004 - Proceedings of the 30th International Conference on Very Large Data Bases. Morgan Kaufmann Publishers, Inc. 2004. p. 816-827. (VLDB 2004 - Proceedings of the 30th International Conference on Very Large Data Bases). doi: 10.1016/b978-012088469-8.50072-3

Object Fusion in Geographic Information Systems

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