Person name recognition using the hybrid approach

Mai Oudah, Khaled Shaalan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Arabic Person Name Recognition has been tackled mostly using either of two approaches: a rule-based or Machine Learning (ML) based approach, with their strengths and weaknesses. In this paper, the problem of Arabic Person Name Recognition is tackled through integrating the two approaches together in a pipelined process to create a hybrid system with the aim of enhancing the overall performance of Person Name Recognition tasks. Extensive experiments are conducted using three different ML classifiers to evaluate the overall performance of the hybrid system. The empirical results indicate that the hybrid approach outperforms both the rule-based and the ML-based approaches. Moreover, our system outperforms the state-of-the-art of Arabic Person Name Recognition in terms of accuracy when applied to ANERcorp dataset, with precision 0.949, recall 0.942 and f-measure 0.945.

Original languageEnglish (US)
Title of host publicationNatural Language Processing and Information Systems - 18th International Conference on Applications of Natural Language to Information Systems, NLDB 2013, Proceedings
Pages237-248
Number of pages12
DOIs
StatePublished - Oct 8 2013
Event18th International Conference on Application of Natural Language to Information Systems, NLDB 2013 - Salford, United Kingdom
Duration: Jun 19 2013Jun 21 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7934 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference18th International Conference on Application of Natural Language to Information Systems, NLDB 2013
CountryUnited Kingdom
CitySalford
Period6/19/136/21/13

Fingerprint

Hybrid Approach
Learning systems
Person
Hybrid systems
Machine Learning
Hybrid Systems
Classifiers
Classifier
Evaluate
Experiments
Experiment

Keywords

  • Hybrid Approach
  • Machine Learning Approach
  • Natural Language Processing
  • Person Name Recognition
  • Rulebased Approach

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Oudah, M., & Shaalan, K. (2013). Person name recognition using the hybrid approach. In Natural Language Processing and Information Systems - 18th International Conference on Applications of Natural Language to Information Systems, NLDB 2013, Proceedings (pp. 237-248). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7934 LNCS). https://doi.org/10.1007/978-3-642-38824-8_20

Person name recognition using the hybrid approach. / Oudah, Mai; Shaalan, Khaled.

Natural Language Processing and Information Systems - 18th International Conference on Applications of Natural Language to Information Systems, NLDB 2013, Proceedings. 2013. p. 237-248 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7934 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Oudah, M & Shaalan, K 2013, Person name recognition using the hybrid approach. in Natural Language Processing and Information Systems - 18th International Conference on Applications of Natural Language to Information Systems, NLDB 2013, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 7934 LNCS, pp. 237-248, 18th International Conference on Application of Natural Language to Information Systems, NLDB 2013, Salford, United Kingdom, 6/19/13. https://doi.org/10.1007/978-3-642-38824-8_20
Oudah M, Shaalan K. Person name recognition using the hybrid approach. In Natural Language Processing and Information Systems - 18th International Conference on Applications of Natural Language to Information Systems, NLDB 2013, Proceedings. 2013. p. 237-248. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-642-38824-8_20
Oudah, Mai ; Shaalan, Khaled. / Person name recognition using the hybrid approach. Natural Language Processing and Information Systems - 18th International Conference on Applications of Natural Language to Information Systems, NLDB 2013, Proceedings. 2013. pp. 237-248 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
@inproceedings{39a3882e34f846edadfdb9909d5a0332,
title = "Person name recognition using the hybrid approach",
abstract = "Arabic Person Name Recognition has been tackled mostly using either of two approaches: a rule-based or Machine Learning (ML) based approach, with their strengths and weaknesses. In this paper, the problem of Arabic Person Name Recognition is tackled through integrating the two approaches together in a pipelined process to create a hybrid system with the aim of enhancing the overall performance of Person Name Recognition tasks. Extensive experiments are conducted using three different ML classifiers to evaluate the overall performance of the hybrid system. The empirical results indicate that the hybrid approach outperforms both the rule-based and the ML-based approaches. Moreover, our system outperforms the state-of-the-art of Arabic Person Name Recognition in terms of accuracy when applied to ANERcorp dataset, with precision 0.949, recall 0.942 and f-measure 0.945.",
keywords = "Hybrid Approach, Machine Learning Approach, Natural Language Processing, Person Name Recognition, Rulebased Approach",
author = "Mai Oudah and Khaled Shaalan",
year = "2013",
month = "10",
day = "8",
doi = "10.1007/978-3-642-38824-8_20",
language = "English (US)",
isbn = "9783642388231",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "237--248",
booktitle = "Natural Language Processing and Information Systems - 18th International Conference on Applications of Natural Language to Information Systems, NLDB 2013, Proceedings",

}

TY - GEN

T1 - Person name recognition using the hybrid approach

AU - Oudah, Mai

AU - Shaalan, Khaled

PY - 2013/10/8

Y1 - 2013/10/8

N2 - Arabic Person Name Recognition has been tackled mostly using either of two approaches: a rule-based or Machine Learning (ML) based approach, with their strengths and weaknesses. In this paper, the problem of Arabic Person Name Recognition is tackled through integrating the two approaches together in a pipelined process to create a hybrid system with the aim of enhancing the overall performance of Person Name Recognition tasks. Extensive experiments are conducted using three different ML classifiers to evaluate the overall performance of the hybrid system. The empirical results indicate that the hybrid approach outperforms both the rule-based and the ML-based approaches. Moreover, our system outperforms the state-of-the-art of Arabic Person Name Recognition in terms of accuracy when applied to ANERcorp dataset, with precision 0.949, recall 0.942 and f-measure 0.945.

AB - Arabic Person Name Recognition has been tackled mostly using either of two approaches: a rule-based or Machine Learning (ML) based approach, with their strengths and weaknesses. In this paper, the problem of Arabic Person Name Recognition is tackled through integrating the two approaches together in a pipelined process to create a hybrid system with the aim of enhancing the overall performance of Person Name Recognition tasks. Extensive experiments are conducted using three different ML classifiers to evaluate the overall performance of the hybrid system. The empirical results indicate that the hybrid approach outperforms both the rule-based and the ML-based approaches. Moreover, our system outperforms the state-of-the-art of Arabic Person Name Recognition in terms of accuracy when applied to ANERcorp dataset, with precision 0.949, recall 0.942 and f-measure 0.945.

KW - Hybrid Approach

KW - Machine Learning Approach

KW - Natural Language Processing

KW - Person Name Recognition

KW - Rulebased Approach

UR - http://www.scopus.com/inward/record.url?scp=84884941005&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84884941005&partnerID=8YFLogxK

U2 - 10.1007/978-3-642-38824-8_20

DO - 10.1007/978-3-642-38824-8_20

M3 - Conference contribution

AN - SCOPUS:84884941005

SN - 9783642388231

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

SP - 237

EP - 248

BT - Natural Language Processing and Information Systems - 18th International Conference on Applications of Natural Language to Information Systems, NLDB 2013, Proceedings

ER -