An empirical study of instance-based ontology matching

Antoine Isaac; Lourens Van Der Meij; Stefan Schlobach; Shenghui Wang

doi:10.1007/978-3-540-76298-0_19

An empirical study of instance-based ontology matching

Antoine Isaac^*, Lourens Van Der Meij, Stefan Schlobach, Shenghui Wang

^*Corresponding author for this work

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

78 Citations (Scopus)

Abstract

Instance-based ontology mapping is a promising family of solutions to a class of ontology alignment problems. It crucially depends on measuring the similarity between sets of annotated instances. In this paper we study how the choice of co-occurrence measures affects the performance of instance-based mapping. To this end, we have implemented a number of different statistical co-occurrence measures. We have prepared an extensive test case using vocabularies of thousands of terms, millions of instances, and hundreds of thousands of co-annotated items. We have obtained a human Gold Standard judgement for part of the mapping-space. We then study how the different co-occurrence measures and a number of algorithmic variations perform on our benchmark dataset as compared against the Gold Standard. Our systematic study shows excellent results of instance-based matching in general, where the more simple measures often outperform more sophisticated statistical co-occurrence measures.

Original language	English
Title of host publication	The Semantic Web
Subtitle of host publication	6th International Semantic Web Conference, 2nd Asian Semantic Web Conference, ISWC 2007 + ASWC 2007, Busan, Korea, November 11-15, 2007. Proceedings
Editors	Karl Aberer
Publisher	Springer
Pages	253-266
Number of pages	14
ISBN (Electronic)	978-3-540-76298-0
ISBN (Print)	978-3-540-76297-3
DOIs	https://doi.org/10.1007/978-3-540-76298-0_19
Publication status	Published - 1 Dec 2007
Externally published	Yes
Event	6th International Semantic Web Conference, ISWC 2007 and 2nd Asian Semantic Web Conference, ASWC 2007 - Busan, Korea, Republic of Duration: 11 Nov 2007 → 15 Nov 2007 Conference number: 6

Publication series

Name	Lecture Notes in Computer Science
Publisher	Springer
Volume	4825
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	6th International Semantic Web Conference, ISWC 2007 and 2nd Asian Semantic Web Conference, ASWC 2007
Abbreviated title	ISWC 2007
Country/Territory	Korea, Republic of
City	Busan
Period	11/11/07 → 15/11/07

Keywords

Information gain
Mapping index
Ontology mapping
Pointwise mutual information
Equivalent concept

Access to Document

10.1007/978-3-540-76298-0_19

Cite this

Isaac, A., Van Der Meij, L., Schlobach, S., & Wang, S. (2007). An empirical study of instance-based ontology matching. In K. Aberer (Ed.), The Semantic Web: 6th International Semantic Web Conference, 2nd Asian Semantic Web Conference, ISWC 2007 + ASWC 2007, Busan, Korea, November 11-15, 2007. Proceedings (pp. 253-266). (Lecture Notes in Computer Science; Vol. 4825). Springer. https://doi.org/10.1007/978-3-540-76298-0_19

Isaac, Antoine ; Van Der Meij, Lourens ; Schlobach, Stefan et al. / An empirical study of instance-based ontology matching. The Semantic Web: 6th International Semantic Web Conference, 2nd Asian Semantic Web Conference, ISWC 2007 + ASWC 2007, Busan, Korea, November 11-15, 2007. Proceedings. editor / Karl Aberer. Springer, 2007. pp. 253-266 (Lecture Notes in Computer Science).

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abstract = "Instance-based ontology mapping is a promising family of solutions to a class of ontology alignment problems. It crucially depends on measuring the similarity between sets of annotated instances. In this paper we study how the choice of co-occurrence measures affects the performance of instance-based mapping. To this end, we have implemented a number of different statistical co-occurrence measures. We have prepared an extensive test case using vocabularies of thousands of terms, millions of instances, and hundreds of thousands of co-annotated items. We have obtained a human Gold Standard judgement for part of the mapping-space. We then study how the different co-occurrence measures and a number of algorithmic variations perform on our benchmark dataset as compared against the Gold Standard. Our systematic study shows excellent results of instance-based matching in general, where the more simple measures often outperform more sophisticated statistical co-occurrence measures.",

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Isaac, A, Van Der Meij, L, Schlobach, S & Wang, S 2007, An empirical study of instance-based ontology matching. in K Aberer (ed.), The Semantic Web: 6th International Semantic Web Conference, 2nd Asian Semantic Web Conference, ISWC 2007 + ASWC 2007, Busan, Korea, November 11-15, 2007. Proceedings. Lecture Notes in Computer Science, vol. 4825, Springer, pp. 253-266, 6th International Semantic Web Conference, ISWC 2007 and 2nd Asian Semantic Web Conference, ASWC 2007, Busan, Korea, Republic of, 11/11/07. https://doi.org/10.1007/978-3-540-76298-0_19

An empirical study of instance-based ontology matching. / Isaac, Antoine; Van Der Meij, Lourens; Schlobach, Stefan et al.
The Semantic Web: 6th International Semantic Web Conference, 2nd Asian Semantic Web Conference, ISWC 2007 + ASWC 2007, Busan, Korea, November 11-15, 2007. Proceedings. ed. / Karl Aberer. Springer, 2007. p. 253-266 (Lecture Notes in Computer Science; Vol. 4825).

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

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AB - Instance-based ontology mapping is a promising family of solutions to a class of ontology alignment problems. It crucially depends on measuring the similarity between sets of annotated instances. In this paper we study how the choice of co-occurrence measures affects the performance of instance-based mapping. To this end, we have implemented a number of different statistical co-occurrence measures. We have prepared an extensive test case using vocabularies of thousands of terms, millions of instances, and hundreds of thousands of co-annotated items. We have obtained a human Gold Standard judgement for part of the mapping-space. We then study how the different co-occurrence measures and a number of algorithmic variations perform on our benchmark dataset as compared against the Gold Standard. Our systematic study shows excellent results of instance-based matching in general, where the more simple measures often outperform more sophisticated statistical co-occurrence measures.

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Isaac A, Van Der Meij L, Schlobach S, Wang S. An empirical study of instance-based ontology matching. In Aberer K, editor, The Semantic Web: 6th International Semantic Web Conference, 2nd Asian Semantic Web Conference, ISWC 2007 + ASWC 2007, Busan, Korea, November 11-15, 2007. Proceedings. Springer. 2007. p. 253-266. (Lecture Notes in Computer Science). doi: 10.1007/978-3-540-76298-0_19

An empirical study of instance-based ontology matching

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Keywords

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