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Improving Ontology Recommendation and Reuse in WebCORE by Collaborative Assessments

Cantador, I.; Fernandez, M. and Castells, P. (2007). Improving Ontology Recommendation and Reuse in WebCORE by Collaborative Assessments. In: Workshop on Social and Collaborative Construction of Structured Knowledge at 16th International World Wide Web Conference (WWW 2007), 08-12 May 2007, Banff, Canada.

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In this work, we present an extension of CORE [8], a tool for Collaborative Ontology Reuse and Evaluation. The system receives an informal description of a specific semantic domain and determines which ontologies from a repository are the most appropriate to describe the given domain. For this task, the environment is divided into three modules. The first component receives the problem description as a set of terms, and allows the user to refine and enlarge it using WordNet. The second module applies multiple automatic criteria to evaluate the ontologies of the repository, and determines which ones fit best the problem description. A ranked list of ontologies is returned for each criterion, and the lists are combined by means of rank fusion techniques. Finally, the third component uses manual user evaluations in order to incorporate a human, collaborative assessment of the ontologies. The new version of the system incorporates several novelties, such as its implementation as a web application; the incorporation of a NLP module to manage the problem definitions; modifications on the automatic ontology retrieval strategies; and a collaborative framework to find potential relevant terms according to previous user queries. Finally, we present some early experiments on ontology retrieval and evaluation, showing the benefits of our system.

Item Type: Conference or Workshop Item
Copyright Holders: 2007 Unknown
Project Funding Details:
Funded Project NameProject IDFunding Body
Not SetNot SetSpanish Ministry of Science and Education [TIN2005-06885 and FPU program]
Keywords: ontology evaluation; ontology reuse; rank fusion; collaborative filtering; WordNet
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Research Group: Centre for Research in Computing (CRC)
Item ID: 28587
Depositing User: Kay Dave
Date Deposited: 17 May 2011 10:36
Last Modified: 13 Dec 2018 07:15
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