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

doi:10.1007/978-3-642-04447-2_10

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

^*Corresponding author for this work

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

8 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 language	English
Title of host publication	Evaluating Systems for Multilingual and Multimodal Information Access - 9th Workshop of the Cross-Language Evaluation Forum, CLEF 2008, Revised Selected Papers
Pages	89-96
Number of pages	8
DOIs	https://doi.org/10.1007/978-3-642-04447-2_10
Publication status	Published - 1 Dec 2009
Externally published	Yes
Event	9th Workshop of the Cross-Language Evaluation Forum, CLEF 2008 - Aarhus, Denmark Duration: 17 Sept 2008 → 19 Sept 2008

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	5706 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	9th Workshop of the Cross-Language Evaluation Forum, CLEF 2008
Country/Territory	Denmark
City	Aarhus
Period	17/09/08 → 19/09/08

Keywords

Natural language
Part of speech
Persian information retrieval

Access to Document

10.1007/978-3-642-04447-2_10

Cite this

Karimpour, R., Ghorbani, A., Pishdad, A., Mohtarami, M., Aleahmad, A., Amiri, H., & Oroumchian, F. (2009). Improving persian information retrieval systems using stemming and part of speech tagging. In Evaluating Systems for Multilingual and Multimodal Information Access - 9th Workshop of the Cross-Language Evaluation Forum, CLEF 2008, Revised Selected Papers (pp. 89-96). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5706 LNCS). https://doi.org/10.1007/978-3-642-04447-2_10

Karimpour, Reza ; Ghorbani, Amineh ; Pishdad, Azadeh et al. / Improving persian information retrieval systems using stemming and part of speech tagging. Evaluating Systems for Multilingual and Multimodal Information Access - 9th Workshop of the Cross-Language Evaluation Forum, CLEF 2008, Revised Selected Papers. 2009. pp. 89-96 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{082d724dc5b646d9b5f428b23923d608,

title = "Improving persian information retrieval systems using stemming and part of speech tagging",

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.",

keywords = "Natural language, Part of speech, Persian information retrieval",

author = "Reza Karimpour and Amineh Ghorbani and Azadeh Pishdad and Mitra Mohtarami and Abolfazl Aleahmad and Hadi Amiri and Farhad Oroumchian",

year = "2009",

month = dec,

day = "1",

doi = "10.1007/978-3-642-04447-2_10",

language = "English",

isbn = "3642044468",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

pages = "89--96",

booktitle = "Evaluating Systems for Multilingual and Multimodal Information Access - 9th Workshop of the Cross-Language Evaluation Forum, CLEF 2008, Revised Selected Papers",

note = "9th Workshop of the Cross-Language Evaluation Forum, CLEF 2008 ; Conference date: 17-09-2008 Through 19-09-2008",

}

Karimpour, R, Ghorbani, A, Pishdad, A, Mohtarami, M, Aleahmad, A, Amiri, H & Oroumchian, F 2009, Improving persian information retrieval systems using stemming and part of speech tagging. in Evaluating Systems for Multilingual and Multimodal Information Access - 9th Workshop of the Cross-Language Evaluation Forum, CLEF 2008, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5706 LNCS, pp. 89-96, 9th Workshop of the Cross-Language Evaluation Forum, CLEF 2008, Aarhus, Denmark, 17/09/08. https://doi.org/10.1007/978-3-642-04447-2_10

Improving persian information retrieval systems using stemming and part of speech tagging. / Karimpour, Reza; Ghorbani, Amineh; Pishdad, Azadeh et al.
Evaluating Systems for Multilingual and Multimodal Information Access - 9th Workshop of the Cross-Language Evaluation Forum, CLEF 2008, Revised Selected Papers. 2009. p. 89-96 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5706 LNCS).

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

TY - GEN

T1 - Improving persian information retrieval systems using stemming and part of speech tagging

AU - Karimpour, Reza

AU - Ghorbani, Amineh

AU - Pishdad, Azadeh

AU - Mohtarami, Mitra

AU - Aleahmad, Abolfazl

AU - Amiri, Hadi

AU - Oroumchian, Farhad

PY - 2009/12/1

Y1 - 2009/12/1

N2 - 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.

AB - 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.

KW - Natural language

KW - Part of speech

KW - Persian information retrieval

UR - http://www.scopus.com/inward/record.url?scp=70549100196&partnerID=8YFLogxK

U2 - 10.1007/978-3-642-04447-2_10

DO - 10.1007/978-3-642-04447-2_10

M3 - Conference contribution

AN - SCOPUS:70549100196

SN - 3642044468

SN - 9783642044465

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 89

EP - 96

BT - Evaluating Systems for Multilingual and Multimodal Information Access - 9th Workshop of the Cross-Language Evaluation Forum, CLEF 2008, Revised Selected Papers

T2 - 9th Workshop of the Cross-Language Evaluation Forum, CLEF 2008

Y2 - 17 September 2008 through 19 September 2008

ER -

Karimpour R, Ghorbani A, Pishdad A, Mohtarami M, Aleahmad A, Amiri H et al. Improving persian information retrieval systems using stemming and part of speech tagging. In Evaluating Systems for Multilingual and Multimodal Information Access - 9th Workshop of the Cross-Language Evaluation Forum, CLEF 2008, Revised Selected Papers. 2009. p. 89-96. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-04447-2_10

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

Abstract

Publication series

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Cite this