A reverse dictionary based on semantic analysis using wordnet

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

17 Scopus citations

Abstract

In this research we present a new approach for reverse dictionary creation, one purely semantic. We focus on a semantic analysis of input phrases using semantic similarity measures to represent words as vectors in a semantic space previously created assisted by WordNet. Then, applying algebraic analysis we select a sample of candidate words which passes through a filtering process and a ranking phase. Finally, a predefined number of output target words are displayed. A test set of 50 input concepts was created in order to evaluate our system, comparing our experimental results against OneLook Reverse Dictionary to demonstrate that our system provides better results over current available implementations.

Original languageEnglish
Title of host publicationAdvances in Artificial Intelligence and Its Applications - 12th Mexican International Conference on Artificial Intelligence, MICAI 2013, Proceedings
Pages275-285
Number of pages11
EditionPART 1
DOIs
StatePublished - 2013
Event12th Mexican International Conference on Artificial Intelligence, MICAI 2013 - Mexico City, Mexico
Duration: 24 Nov 201330 Nov 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume8265 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference12th Mexican International Conference on Artificial Intelligence, MICAI 2013
Country/TerritoryMexico
CityMexico City
Period24/11/1330/11/13

Keywords

  • Reverse dictionary
  • Search by concept
  • Semantic analysis
  • Vector space model

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