Mining Linked Open Data for Semantic Predications to Inform Literature-Based Knowledge Discovery

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Description

This paper proposes to source semantic predications from Linked Open Data to provide the context of the relationships between the entities extracted from scholarly literature.

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2 p.

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Padova, Kathleen J. November 9, 2018.

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This paper is part of the collection entitled: International Conference on Knowledge Management (ICKM), 2017 and was provided by UNT College of Information to Digital Library, a digital repository hosted by the UNT Libraries. More information about this paper can be viewed below.

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Description

This paper proposes to source semantic predications from Linked Open Data to provide the context of the relationships between the entities extracted from scholarly literature.

Physical Description

2 p.

Notes

Abstract: Recent research into Literature-Based Knowledge Discovery (LBKD) has been focusing on extracting and identifying the context of relationships between discovered concepts. That is, it seeks to determine a positive, negative, or even the specific nature of the relationship or influence between two concepts. For example, in the seminal paper introducing the practice and applicability of LBKD, Swanson (1986) was able to identify the connection between Dietary Fish Oil and Platelet Aggregation, and Platelet Aggregation and Reynaud’s Syndrome; but his initial technique was not able to identify that Dietary Fish Oil reduces platelet aggregation or that Platelet Aggregation is a symptom of Reynaud’s Syndrome. These contextual relationships are expressed in a form sometimes called semantic predications (subject-predicate-object) and are often in RDF triplestore standard format. My research proposes to source semantic predications from Linked Open Data to provide the context of the relationships between the entities extracted from scholarly literature.

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  • 14th International Conference on Knowledge Management, November 9-10, 2018. Vancouver, Canada.

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International Conference on Knowledge Management (ICKM), 2017

The 13th International Conference on Knowledge Management (ICKM) met October 25-26 in Dallas, Texas. Serving as digital proceedings, this collection includes papers, posters, and slides from invited talks as well as practitioner and sponsor presentations.

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Creation Date

  • November 9, 2018

Added to The UNT Digital Library

  • Dec. 19, 2018, 12:07 p.m.

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Padova, Kathleen J. Mining Linked Open Data for Semantic Predications to Inform Literature-Based Knowledge Discovery, paper, November 9, 2018; (digital.library.unt.edu/ark:/67531/metadc1393762/: accessed January 24, 2019), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT College of Information.