Name
Title | ||
|---|---|---|
An information theoretic approach to improve semantic similarity assessments across multiple ontologies. |
Abstract | ||
|---|---|---|
•A method based on information content to accurately compute semantic similarity of concepts in different ontologies.•A quantification of the degree of semantic equivalence between concept pairs.•The informativeness of concepts and concept pairs is computed intrinsically from taxonomic knowledge.•The evaluation has been performed with several widespread biomedical benchmarks and ontologies.•Results show a significant improvement of similarity accuracy in comparison with related works. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1016/j.ins.2014.06.039 | Information Sciences |
Keywords | Field | DocType |
Semantic similarity,Information Theory,Ontology,MeSH,SNOMED-CT | Information theory,Ontology (information science),Semantic similarity,Ontology-based data integration,Ontology,Information retrieval,Computer science,Similarity heuristic,Upper ontology,SNOMED CT | Journal |
Volume | ISSN | Citations |
283 | 0020-0255 | 11 |
PageRank | References | Authors |
0.51 | 56 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Montserrat Batet | 1 | 899 | 37.20 |
| Sébastien Harispe | 2 | 107 | 11.23 |
| Sylvie Ranwez | 3 | 232 | 26.23 |
| David Sánchez | 4 | 395 | 32.93 |
| Vincent Ranwez | 5 | 310 | 20.35 |