A hybrid approach to features representation for fine-Grained Arabic named entity recognition

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

Standard

A hybrid approach to features representation for fine-Grained Arabic named entity recognition. / Alotaibi, Fahd; Lee, Mark.

COLING 2014 - 25th International Conference on Computational Linguistics, Proceedings of COLING 2014: Technical Papers. Association for Computational Linguistics, ACL, 2014. p. 984-995.

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

Harvard

Alotaibi, F & Lee, M 2014, A hybrid approach to features representation for fine-Grained Arabic named entity recognition. in COLING 2014 - 25th International Conference on Computational Linguistics, Proceedings of COLING 2014: Technical Papers. Association for Computational Linguistics, ACL, pp. 984-995, 25th International Conference on Computational Linguistics, COLING 2014, Dublin, Ireland, 23/08/14.

APA

Alotaibi, F., & Lee, M. (2014). A hybrid approach to features representation for fine-Grained Arabic named entity recognition. In COLING 2014 - 25th International Conference on Computational Linguistics, Proceedings of COLING 2014: Technical Papers (pp. 984-995). Association for Computational Linguistics, ACL.

Vancouver

Alotaibi F, Lee M. A hybrid approach to features representation for fine-Grained Arabic named entity recognition. In COLING 2014 - 25th International Conference on Computational Linguistics, Proceedings of COLING 2014: Technical Papers. Association for Computational Linguistics, ACL. 2014. p. 984-995

Author

Alotaibi, Fahd ; Lee, Mark. / A hybrid approach to features representation for fine-Grained Arabic named entity recognition. COLING 2014 - 25th International Conference on Computational Linguistics, Proceedings of COLING 2014: Technical Papers. Association for Computational Linguistics, ACL, 2014. pp. 984-995

Bibtex

@inproceedings{608beab6fe0a4fc48e7dc77d69858673,
title = "A hybrid approach to features representation for fine-Grained Arabic named entity recognition",
abstract = "Despite considerable research on the topic of Arabic Named Entity Recognition (NER), almost all efforts focus on a traditional set of semantic classes, features and token representations. In this work, we advance previous research in a systematic manner and devise a novel method to represent these features, relying on a dependency-based structure to capture further evidence within the sentence. Moreover, the work also describes an evaluation of the method involving the capture of global features and employing the clustering of unannotated textual data. To meet this set of goals, we conducted a series of evaluations to evaluate different aspects that demonstrate great improvement when compared with the baseline model.",
author = "Fahd Alotaibi and Mark Lee",
year = "2014",
month = jan,
day = "1",
language = "English",
pages = "984--995",
booktitle = "COLING 2014 - 25th International Conference on Computational Linguistics, Proceedings of COLING 2014",
publisher = "Association for Computational Linguistics, ACL",
note = "25th International Conference on Computational Linguistics, COLING 2014 ; Conference date: 23-08-2014 Through 29-08-2014",

}

RIS

TY - GEN

T1 - A hybrid approach to features representation for fine-Grained Arabic named entity recognition

AU - Alotaibi, Fahd

AU - Lee, Mark

PY - 2014/1/1

Y1 - 2014/1/1

N2 - Despite considerable research on the topic of Arabic Named Entity Recognition (NER), almost all efforts focus on a traditional set of semantic classes, features and token representations. In this work, we advance previous research in a systematic manner and devise a novel method to represent these features, relying on a dependency-based structure to capture further evidence within the sentence. Moreover, the work also describes an evaluation of the method involving the capture of global features and employing the clustering of unannotated textual data. To meet this set of goals, we conducted a series of evaluations to evaluate different aspects that demonstrate great improvement when compared with the baseline model.

AB - Despite considerable research on the topic of Arabic Named Entity Recognition (NER), almost all efforts focus on a traditional set of semantic classes, features and token representations. In this work, we advance previous research in a systematic manner and devise a novel method to represent these features, relying on a dependency-based structure to capture further evidence within the sentence. Moreover, the work also describes an evaluation of the method involving the capture of global features and employing the clustering of unannotated textual data. To meet this set of goals, we conducted a series of evaluations to evaluate different aspects that demonstrate great improvement when compared with the baseline model.

UR - http://www.scopus.com/inward/record.url?scp=84959911252&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:84959911252

SP - 984

EP - 995

BT - COLING 2014 - 25th International Conference on Computational Linguistics, Proceedings of COLING 2014

PB - Association for Computational Linguistics, ACL

T2 - 25th International Conference on Computational Linguistics, COLING 2014

Y2 - 23 August 2014 through 29 August 2014

ER -