Improving persian information retrieval systems using stemming and part of speech tagging

Reza Karimpour, Amineh Ghorbani, Azadeh Pishdad, Mitra Mohtarami, Abolfazl Aleahmad, Hadi Amiri, Farhad Oroumchian

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

5 Citations (Scopus)

Abstract

With the emergence of vast resources of information, it is necessary to develop methods that retrieve the most relevant information according to needs. These retrieval methods may benefit from natural language constructs to boost their results by achieving higher precision and recall rates. In this study, we have used part of speech properties of terms as extra source of information about document and query terms and have evaluated the impact of such data on the performance of the Persian retrieval algorithms. Furthermore the effect of stemming has been experimented as a complement to this research. Our findings indicate that part of speech tags may have small influence on effectiveness of the retrieved results. However, when this information is combined with stemming it improves the accuracy of the outcomes considerably.

Original languageEnglish
Title of host publicationEvaluating Systems for Multilingual and Multimodal Information Access - 9th Workshop of the Cross-Language Evaluation Forum, CLEF 2008, Revised Selected Papers
Pages89-96
Number of pages8
DOIs
Publication statusPublished - 1 Dec 2009
Externally publishedYes
Event9th Workshop of the Cross-Language Evaluation Forum, CLEF 2008 - Aarhus, Denmark
Duration: 17 Sep 200819 Sep 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5706 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference9th Workshop of the Cross-Language Evaluation Forum, CLEF 2008
CountryDenmark
CityAarhus
Period17/09/0819/09/08

Keywords

  • Natural language
  • Part of speech
  • Persian information retrieval

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