Exploiting taxonomical knowledge to compute semantic similarity: an evaluation in the biomedical domain

Authors:
Montserrat Batet;David Sanchez;Aida Valls;Karina Gibert
Affiliations:
Universitat Rovira i Virgili, Department of Computer Science and Mathematics, Tarragona, Catalonia, Spain;Universitat Rovira i Virgili, Department of Computer Science and Mathematics, Tarragona, Catalonia, Spain;Universitat Rovira i Virgili, Department of Computer Science and Mathematics, Tarragona, Catalonia, Spain;Universitat Politècnica de Catalunya, Department of Statistics and Operations Research, Barcelona, Catalonia, Spain
Venue:
IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part I
Year:
2010

Citing 10
Cited 2

Enabling technology for knowledge sharing

AI Magazine
An Information-Theoretic Definition of Similarity

ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Verbs semantics and lexical selection

ACL '94 Proceedings of the 32nd annual meeting on Association for Computational Linguistics
Towards the development of a conceptual distance metric for the UMLS

Journal of Biomedical Informatics
Ontology Learning and Population from Text: Algorithms, Evaluation and Applications

Ontology Learning and Population from Text: Algorithms, Evaluation and Applications
Measures of semantic similarity and relatedness in the biomedical domain

Journal of Biomedical Informatics
The Google Similarity Distance

IEEE Transactions on Knowledge and Data Engineering
Learning non-taxonomic relationships from web documents for domain ontology construction

Data & Knowledge Engineering
Using information content to evaluate semantic similarity in a taxonomy

IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Unsupervised named-entity extraction from the Web: An experimental study

Artificial Intelligence

The Role of Ontologies in the Anonymization of Textual Variables

Proceedings of the 2010 conference on Artificial Intelligence Research and Development: Proceedings of the 13th International Conference of the Catalan Association for Artificial Intelligence
Semantic Clustering Using Multiple Ontologies

Proceedings of the 2010 conference on Artificial Intelligence Research and Development: Proceedings of the 13th International Conference of the Catalan Association for Artificial Intelligence

Quantified Score

Hi-index	0.00

Visualization

Abstract

Determining the semantic similarity between concept pairs is an important task in many language related problems. In the biomedical field, several approaches to assess the semantic similarity between concepts by exploiting the knowledge provided by a domain ontology have been proposed. In this paper, some of those approaches are studied, exploiting the taxonomical structure of a biomedical ontology (SNOMEDCT). Then, a new measure is presented based on computing the amount of overlapping and non-overlapping taxonomical knowledge between concept pairs. The performance of our proposal is compared against related ones using a set of standard benchmarks of manually ranked terms. The correlation between the results obtained by the computerized approaches and the manual ranking shows that our proposal clearly outperforms previous works.