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Searching Ontologies Based on Content: Experiments in the Biomedical Domain

Searching Ontologies Based on Content: Experiments in the Biomedical Domain
Searching Ontologies Based on Content: Experiments in the Biomedical Domain
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.
Alani, Harith
70cdbdce-1494-44c2-9dae-65d82bf7e991
Noy, Natasha
be0dac66-5026-466b-82aa-6b427cb211e3
Shah, Nigam
45da7674-669f-4f6c-94e7-80a458d30bf0
Shadbolt, Nigel
5c5acdf4-ad42-49b6-81fe-e9db58c2caf7
Musen, Mark
1b90eb45-8f97-45d7-a700-fd041afbdf0a
Alani, Harith
70cdbdce-1494-44c2-9dae-65d82bf7e991
Noy, Natasha
be0dac66-5026-466b-82aa-6b427cb211e3
Shah, Nigam
45da7674-669f-4f6c-94e7-80a458d30bf0
Shadbolt, Nigel
5c5acdf4-ad42-49b6-81fe-e9db58c2caf7
Musen, Mark
1b90eb45-8f97-45d7-a700-fd041afbdf0a

Alani, Harith, Noy, Natasha, Shah, Nigam, Shadbolt, Nigel and Musen, Mark (2007) Searching Ontologies Based on Content: Experiments in the Biomedical Domain. The Fourth International Conference on Knowledge Capture (K-Cap), Canada.

Record type: Conference or Workshop Item (Paper)

Abstract

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.

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More information

Published date: 2007
Additional Information: Event Dates: October
Venue - Dates: The Fourth International Conference on Knowledge Capture (K-Cap), Canada, 2007-10-01
Organisations: Web & Internet Science

Identifiers

Local EPrints ID: 262069
URI: http://eprints.soton.ac.uk/id/eprint/262069
PURE UUID: e75f7929-b525-45e2-b7af-569bb9a30819

Catalogue record

Date deposited: 24 Aug 2007
Last modified: 02 Dec 2019 21:07

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