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Searching ontologies based on content: Experiments in the biomedical domain

Alani, Harith; Noy, Natasha; Shah, Nigam; Shadbolt, Nigel and Musen, Mark (2007). Searching ontologies based on content: Experiments in the biomedical domain. In: The Fourth International Conference on Knowledge Capture (K-Cap), 28-31 Oct 2007, Whistler, Canada.


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As more ontologies become publicly available, finding the "right" ontologies becomes much harder. In this paper, we address the problem of ontology search: finding a collection of ontologies from an ontology repository that are relevant to the user's query. In particular, we look at the case when users search for ontologies relevant to a particular topic (e.g., an ontology about anatomy). Ontologies that are most relevant to such query often do not have the query term in the names of their concepts (e.g., the Foundational Model of Anatomy ontology does not have the term "anatomy" in any of its concepts' names). Thus, we present a new ontology-search technique that helps users in these types of searches. When looking for ontologies on a particular topic (e.g., anatomy), we retrieve from the Web a collection of terms that represent the given domain (e.g., terms such as body, brain, skin, etc. for anatomy). We then use these terms to expand the user query. We evaluate our algorithm on queries for topics in the biomedical domain against a repository of biomedical ontologies. We use the results obtained from experts in the biomedical-ontology domain as the gold standard. Our experiments demonstrate that using our method for query expansion improves retrieval results by a 113%, compared to the tools that search only for the user query terms and consider only class and property names (like Swoogle). We show 43% improvement for the case where not only class and property names but also property values are taken into account.

Item Type: Conference or Workshop Item
Copyright Holders: 2007 The Authors
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: 20026
Depositing User: Harith Alani
Date Deposited: 15 Apr 2010 14:01
Last Modified: 15 Dec 2018 13:13
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