Semantic query extension through probabilistic description logics

Jośe Eduardo Ochoa Luna; Kate Revoredo; Fabio Gagliardi Cozman

Semantic query extension through probabilistic description logics

Jośe Eduardo Ochoa Luna, Kate Revoredo, Fabio Gagliardi Cozman

Research output: Contribution to conference › Conference Paper

1 Scopus citations

Abstract

This paper presents a novel approach for semantic query extension using a probabilistic description logic. Concepts that are related to a keyword-based query are used for finding other concepts and relations through the use of a relational Bayesian network built using the probabilistic description logic crALC. Furthermore, probabilistic assessments allow us to rank the information returned by search. Examples and issues of importance in real world applications are discussed.

Original language	American English
Pages	49-60
Number of pages	12
State	Published - 1 Dec 2010
Externally published	Yes
Event	CEUR Workshop Proceedings - Duration: 1 Jan 2016 → …

Conference

Conference	CEUR Workshop Proceedings
Period	1/01/16 → …

Cite this

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title = "Semantic query extension through probabilistic description logics",

abstract = "This paper presents a novel approach for semantic query extension using a probabilistic description logic. Concepts that are related to a keyword-based query are used for finding other concepts and relations through the use of a relational Bayesian network built using the probabilistic description logic crALC. Furthermore, probabilistic assessments allow us to rank the information returned by search. Examples and issues of importance in real world applications are discussed.",

author = "Luna, {Jo{\'s}e Eduardo Ochoa} and Kate Revoredo and Cozman, {Fabio Gagliardi}",

year = "2010",

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day = "1",

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T1 - Semantic query extension through probabilistic description logics

AU - Luna, Jośe Eduardo Ochoa

AU - Revoredo, Kate

AU - Cozman, Fabio Gagliardi

PY - 2010/12/1

Y1 - 2010/12/1

N2 - This paper presents a novel approach for semantic query extension using a probabilistic description logic. Concepts that are related to a keyword-based query are used for finding other concepts and relations through the use of a relational Bayesian network built using the probabilistic description logic crALC. Furthermore, probabilistic assessments allow us to rank the information returned by search. Examples and issues of importance in real world applications are discussed.

AB - This paper presents a novel approach for semantic query extension using a probabilistic description logic. Concepts that are related to a keyword-based query are used for finding other concepts and relations through the use of a relational Bayesian network built using the probabilistic description logic crALC. Furthermore, probabilistic assessments allow us to rank the information returned by search. Examples and issues of importance in real world applications are discussed.

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M3 - Conference Paper

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T2 - CEUR Workshop Proceedings

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ER -

Semantic query extension through probabilistic description logics

Abstract

Conference

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