Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4961836 | Procedia Computer Science | 2016 | 10 Pages |
Abstract
Even though the calculation of the semantic similarity between textual entities has received a lot of attention by the research community, the more general notion of semantic relatedness (which considers both taxonomic and non-taxonomic knowledge) has been significantly less studied and, in general, stays one step behind in terms of accuracy. In this paper, we improve semantic relatedness assessments by aggregating the highly-accurate ontology-based estimation of semantic similarity with the distributional resemblance of textual terms computed from large textual corpora. As a result, our approach is able to improve the accuracy of related works on a standard benchmark.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science (General)
Authors
Montserrat Batet, David Sánchez,