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

Muhidin Mohamed, Mourad Oussalah

Research output: Contribution to conferencePaper

Abstract

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.
Original languageEnglish
Pages37-42
Publication statusPublished - 23 Aug 2014

Bibliographical note

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/

Fingerprint Dive into the research topics of 'A comparative study of conversion aided methods for WordNet sentence textual similarity'. Together they form a unique fingerprint.

  • Cite this