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Merging Controlled Vocabularies for More Efficient Subject-Based IR Systems

Merging Controlled Vocabularies for More Efficient Subject-Based IR Systems

Ioannis Papadakis, Konstantinos Kyprianos
Copyright: © 2013 |Pages: 14
ISBN13: 9781466624856|ISBN10: 146662485X|EISBN13: 9781466624863
DOI: 10.4018/978-1-4666-2485-6.ch015
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MLA

Papadakis, Ioannis, and Konstantinos Kyprianos. "Merging Controlled Vocabularies for More Efficient Subject-Based IR Systems." Dynamic Models for Knowledge-Driven Organizations, edited by Murray E. Jennex, IGI Global, 2013, pp. 254-267. https://doi.org/10.4018/978-1-4666-2485-6.ch015

APA

Papadakis, I. & Kyprianos, K. (2013). Merging Controlled Vocabularies for More Efficient Subject-Based IR Systems. In M. Jennex (Ed.), Dynamic Models for Knowledge-Driven Organizations (pp. 254-267). IGI Global. https://doi.org/10.4018/978-1-4666-2485-6.ch015

Chicago

Papadakis, Ioannis, and Konstantinos Kyprianos. "Merging Controlled Vocabularies for More Efficient Subject-Based IR Systems." In Dynamic Models for Knowledge-Driven Organizations, edited by Murray E. Jennex, 254-267. Hershey, PA: IGI Global, 2013. https://doi.org/10.4018/978-1-4666-2485-6.ch015

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Abstract

One of the most important tasks of a librarian is the assignment of appropriate subject(s) to a resource within a library’s collection. The subjects usually belong to a controlled vocabulary that is specifically designed for such a task. The most widely adopted controlled vocabulary across libraries around the world is the Library of Congress Subject Headings (LCSH). However, there seems to be a shifting from traditional LCSH to modern thesauri. In this paper, a methodology is proposed, capable of incorporating thesauri into existing LCSH-based Information Retrieval–IR systems. In order to achieve this, a mapping methodology is proposed capable of providing a common structure consisting of terms belonging to LCSH and/or a thesaurus. The structure is modeled as a Simple Knowledge Organization System (SKOS) ontology, which can be employed by appropriate subject-based IR systems. As a proof of concept, the proposed methodology is applied to the DSpace-based University of Piraeus digital library.

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