Name
Title | ||
|---|---|---|
A semantic similarity method based on information content exploiting multiple ontologies |
Abstract | ||
|---|---|---|
The quantification of the semantic similarity between terms is an important research area that configures a valuable tool for text understanding. Among the different paradigms used by related works to compute semantic similarity, in recent years, information theoretic approaches have shown promising results by computing the information content (IC) of concepts from the knowledge provided by ontologies. These approaches, however, are hampered by the coverage offered by the single input ontology. In this paper, we propose extending IC-based similarity measures by considering multiple ontologies in an integrated way. Several strategies are proposed according to which ontology the evaluated terms belong. Our proposal has been evaluated by means of a widely used benchmark of medical terms and MeSH and SNOMED CT as ontologies. Results show an improvement in the similarity assessment accuracy when multiple ontologies are considered. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1016/j.eswa.2012.08.049 | Expert Syst. Appl. |
Keywords | Field | DocType |
semantic similarity,similarity assessment accuracy,snomed ct,different paradigm,single input ontology,semantic similarity method,information content,ic-based similarity measure,important research area,information theoretic approach,multiple ontology,ontologies | Semantic similarity,Ontology (information science),Ontology,Data mining,Information retrieval,Computer science,IDEF5,SNOMED CT | Journal |
Volume | Issue | ISSN |
40 | 4 | 0957-4174 |
Citations | PageRank | References |
30 | 0.76 | 36 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| David Sánchez | 1 | 690 | 33.01 |
| Montserrat Batet | 2 | 899 | 37.20 |