A comparative study of conversion aided methods for WordNet sentence textual similarity


In this paper, we present a comparison of three methods for taxonomic-based sentence semantic relatedness, aided with word parts of speech (PoS) conversion. We use WordNet ontology for determining word level semantic similarity while augmenting WordNet with two other lexicographical databases; namely Categorial Variation Database (CatVar) and Morphosemantic Database in assisting the word category conversion. Using a human annotated benchmark data set, all the three approaches achieved a high positive correlation reaching up to (r = 0.881647) with comparison to human ratings and two other baselines evaluated on the same benchmark data set.

Divisions: College of Engineering & Physical Sciences
College of Engineering & Physical Sciences > School of Informatics and Digital Engineering > Computer Science
Additional Information: This work is licensed under a Creative Commons Attribution 4.0 International License. Page numbers and proceedings footer are added by the organizers. License details: http://creativecommons.org/licenses/by/4.0/
Full Text Link:
Related URLs: https://www.acl ... hology/W14-4507 (Publisher URL)
PURE Output Type: Paper
Published Date: 2014-08-23
Authors: Mohamed, Muhidin
Oussalah, Mourad



Version: Published Version

License: Creative Commons Attribution

| Preview

Export / Share Citation


Additional statistics for this record