A framework for semantic-based similarity measures for ELH-concepts

Karsten Lehmann; Anni Yasmin Turhan

doi:10.1007/978-3-642-33353-8_24

A framework for semantic-based similarity measures for ELH-concepts

Karsten Lehmann^*, Anni Yasmin Turhan

^*Corresponding author for this work

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

50 Citations (Scopus)

Abstract

Similarity measures for concepts written in Description Logics (DLs) are often devised based on the syntax of concepts or simply by adjusting them to a set of instance data. These measures do not take the semantics of the concepts into account and can thus lead to unintuitive results. It even remains unclear how these measures behave if applied to new domains or new sets of instance data. In this paper we develop a framework for similarity measures for ELH-concept descriptions based on the semantics of the DL ELH. We show that our framework ensures that the measures resulting from instantiations fulfill fundamental properties , such as equivalence invariance, yet the framework provides the flexibility to adjust measures to specifics of the modelled domain.

Original language	English
Title of host publication	Logics in Artificial Intelligence - 13th European Conference, JELIA 2012, Proceedings
Pages	307-319
Number of pages	13
DOIs	https://doi.org/10.1007/978-3-642-33353-8_24
Publication status	Published - 2012
Event	13th European Conference on Logics in Artificial Intelligence, JELIA 2012 - Toulouse, France Duration: 26 Sept 2012 → 28 Sept 2012

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	7519 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	13th European Conference on Logics in Artificial Intelligence, JELIA 2012
Country/Territory	France
City	Toulouse
Period	26/09/12 → 28/09/12

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10.1007/978-3-642-33353-8_24

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Lehmann, K., & Turhan, A. Y. (2012). A framework for semantic-based similarity measures for ELH-concepts. In Logics in Artificial Intelligence - 13th European Conference, JELIA 2012, Proceedings (pp. 307-319). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7519 LNAI). https://doi.org/10.1007/978-3-642-33353-8_24

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title = "A framework for semantic-based similarity measures for ELH-concepts",

abstract = "Similarity measures for concepts written in Description Logics (DLs) are often devised based on the syntax of concepts or simply by adjusting them to a set of instance data. These measures do not take the semantics of the concepts into account and can thus lead to unintuitive results. It even remains unclear how these measures behave if applied to new domains or new sets of instance data. In this paper we develop a framework for similarity measures for ELH-concept descriptions based on the semantics of the DL ELH. We show that our framework ensures that the measures resulting from instantiations fulfill fundamental properties , such as equivalence invariance, yet the framework provides the flexibility to adjust measures to specifics of the modelled domain.",

author = "Karsten Lehmann and Turhan, {Anni Yasmin}",

year = "2012",

doi = "10.1007/978-3-642-33353-8_24",

language = "English",

isbn = "9783642333521",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

pages = "307--319",

booktitle = "Logics in Artificial Intelligence - 13th European Conference, JELIA 2012, Proceedings",

note = "13th European Conference on Logics in Artificial Intelligence, JELIA 2012 ; Conference date: 26-09-2012 Through 28-09-2012",

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Lehmann, K & Turhan, AY 2012, A framework for semantic-based similarity measures for ELH-concepts. in Logics in Artificial Intelligence - 13th European Conference, JELIA 2012, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 7519 LNAI, pp. 307-319, 13th European Conference on Logics in Artificial Intelligence, JELIA 2012, Toulouse, France, 26/09/12. https://doi.org/10.1007/978-3-642-33353-8_24

A framework for semantic-based similarity measures for ELH-concepts. / Lehmann, Karsten; Turhan, Anni Yasmin.
Logics in Artificial Intelligence - 13th European Conference, JELIA 2012, Proceedings. 2012. p. 307-319 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7519 LNAI).

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

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AU - Turhan, Anni Yasmin

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AB - Similarity measures for concepts written in Description Logics (DLs) are often devised based on the syntax of concepts or simply by adjusting them to a set of instance data. These measures do not take the semantics of the concepts into account and can thus lead to unintuitive results. It even remains unclear how these measures behave if applied to new domains or new sets of instance data. In this paper we develop a framework for similarity measures for ELH-concept descriptions based on the semantics of the DL ELH. We show that our framework ensures that the measures resulting from instantiations fulfill fundamental properties , such as equivalence invariance, yet the framework provides the flexibility to adjust measures to specifics of the modelled domain.

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DO - 10.1007/978-3-642-33353-8_24

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T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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BT - Logics in Artificial Intelligence - 13th European Conference, JELIA 2012, Proceedings

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Y2 - 26 September 2012 through 28 September 2012

ER -

A framework for semantic-based similarity measures for ELH-concepts

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