Institutional Repository [SANDBOX]
Technical University of Crete
EN  |  EL

Search

Browse

My Space

Design and evaluation of semantic similarity measures for concepts stemming from the same or different ontologies

Petrakis Evripidis, Chliaoutakis Angelos, Raftopoulou Paraskevi, Varelas Giannis

Full record


URI: http://purl.tuc.gr/dl/dias/6A7C20A8-38B2-4254-B0DD-FE5CBCDDD47E
Year 2006
Type of Item Conference Paper Abstract
License
Details
Bibliographic Citation Euripides G.M. Petrakis, Giannis Varelas, Angelos Hliaoutakis, Paraskevi Raftopoulou. (2006, Jun.). Design and Evaluation of Semantic Similarity Measures for Concepts Stemming from the Same or Different Ontologies. Presented at 4th Intern. Workshop on Multimedia Semantics (WMS'06). [Online]. Available: http://www.intelligence.tuc.gr/~petrakis/publications/WMS06.pdf
Appears in Collections

Summary

Semantic Similarity relates to computing the similarity between concepts (terms) which are not necessarily lexically similar. We investigate approaches to computing semantic similarity by mapping terms to an ontology and by examining their relationships in that ontology. More specifically, we investigate approachesto computing the semantic similarity between natural language terms (using WordNet as the underlying reference ontology) and between medical terms (using the MeSH ontology of medical and biomedical terms). The most popular semantic similarity methods are implemented and evaluated using WordNet andMeSH. The focus of this work is also on cross ontology methods which are capable of computing the semantic similarity between terms stemming from different ontologies (WordNet and MeSH in this work). This is a far more difficult problem (than the single ontology one referred to above) which has not been investigated adequately in the literature. X-Similarity, a novel cross-ontology similarity method is also acontribution of this work. All methods examined in this work are integrated into a semantic similarity system which is accessible on the Web.

Services

Statistics