Hierarchical N-gram algorithm for extracting Arabic entities

Eslam Amer; Heba M. Khalil; Tarek El-Shistawy

doi:10.1145/2908446.2908449

Hierarchical N-gram algorithm for extracting Arabic entities

Eslam Amer, Heba M. Khalil, Tarek El-Shistawy

School of Computing

Benha University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Entities Extraction becomes very important for developing many applications of Natural Language Processing (NLP). In this paper, we present a new algorithm to extract entities from Arabic text. The approach uses the semi-structured knowledge source: Arabic Wikipedia to predict the words that constitutes an Arabic entity. Our method is generic and can be applied directly to other languages to extract entities. The proposed method has been designed to analyze Arabic text hierarchically with variable length N-gram. The experimental results have proven that the proposed system is very efficient in detecting entities from large set of Arabic news.

Original language	English
Title of host publication	International Conference on Informatics and Systems, INFOS 2016
Subtitle of host publication	Proceedings of the 10th International Conference on Informatics and Systems
Publisher	Association for Computing Machinery (ACM)
Pages	56-60
Number of pages	5
ISBN (Electronic)	9781450340625
DOIs	https://doi.org/10.1145/2908446.2908449
Publication status	Published - 9 May 2016
Event	10th International Conference on Informatics and Systems, INFOS 2016 - Cairo, Egypt Duration: 9 May 2016 → 11 May 2016

Conference

Conference	10th International Conference on Informatics and Systems, INFOS 2016
Country/Territory	Egypt
City	Cairo
Period	9/05/16 → 11/05/16

Keywords

Arabic Wikipedia
Entity
Information extraction
N-gram
Natural language processing

Access to Document

10.1145/2908446.2908449

Cite this

@inproceedings{f100069bff0942f5b7af1e6023b67c85,

title = "Hierarchical N-gram algorithm for extracting Arabic entities",

abstract = "Entities Extraction becomes very important for developing many applications of Natural Language Processing (NLP). In this paper, we present a new algorithm to extract entities from Arabic text. The approach uses the semi-structured knowledge source: Arabic Wikipedia to predict the words that constitutes an Arabic entity. Our method is generic and can be applied directly to other languages to extract entities. The proposed method has been designed to analyze Arabic text hierarchically with variable length N-gram. The experimental results have proven that the proposed system is very efficient in detecting entities from large set of Arabic news.",

keywords = "Arabic Wikipedia, Entity, Information extraction, N-gram, Natural language processing",

author = "Eslam Amer and Khalil, {Heba M.} and Tarek El-Shistawy",

note = "Publisher Copyright: {\textcopyright} 2016 ACM. Noissn.; 10th International Conference on Informatics and Systems, INFOS 2016 ; Conference date: 09-05-2016 Through 11-05-2016",

year = "2016",

month = may,

day = "9",

doi = "10.1145/2908446.2908449",

language = "English",

pages = "56--60",

booktitle = "International Conference on Informatics and Systems, INFOS 2016",

publisher = "Association for Computing Machinery (ACM)",

address = "United States",

}

Amer, E, Khalil, HM & El-Shistawy, T 2016, Hierarchical N-gram algorithm for extracting Arabic entities. in International Conference on Informatics and Systems, INFOS 2016: Proceedings of the 10th International Conference on Informatics and Systems., 2908449, Association for Computing Machinery (ACM), pp. 56-60, 10th International Conference on Informatics and Systems, INFOS 2016, Cairo, Egypt, 9/05/16. https://doi.org/10.1145/2908446.2908449

Hierarchical N-gram algorithm for extracting Arabic entities. / Amer, Eslam; Khalil, Heba M.; El-Shistawy, Tarek.
International Conference on Informatics and Systems, INFOS 2016: Proceedings of the 10th International Conference on Informatics and Systems. Association for Computing Machinery (ACM), 2016. p. 56-60 2908449.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Hierarchical N-gram algorithm for extracting Arabic entities

AU - Amer, Eslam

AU - Khalil, Heba M.

AU - El-Shistawy, Tarek

PY - 2016/5/9

Y1 - 2016/5/9

N2 - Entities Extraction becomes very important for developing many applications of Natural Language Processing (NLP). In this paper, we present a new algorithm to extract entities from Arabic text. The approach uses the semi-structured knowledge source: Arabic Wikipedia to predict the words that constitutes an Arabic entity. Our method is generic and can be applied directly to other languages to extract entities. The proposed method has been designed to analyze Arabic text hierarchically with variable length N-gram. The experimental results have proven that the proposed system is very efficient in detecting entities from large set of Arabic news.

AB - Entities Extraction becomes very important for developing many applications of Natural Language Processing (NLP). In this paper, we present a new algorithm to extract entities from Arabic text. The approach uses the semi-structured knowledge source: Arabic Wikipedia to predict the words that constitutes an Arabic entity. Our method is generic and can be applied directly to other languages to extract entities. The proposed method has been designed to analyze Arabic text hierarchically with variable length N-gram. The experimental results have proven that the proposed system is very efficient in detecting entities from large set of Arabic news.

KW - Arabic Wikipedia

KW - Entity

KW - Information extraction

KW - N-gram

KW - Natural language processing

UR - http://www.scopus.com/inward/record.url?scp=84998673791&partnerID=8YFLogxK

U2 - 10.1145/2908446.2908449

DO - 10.1145/2908446.2908449

M3 - Conference contribution

AN - SCOPUS:84998673791

SP - 56

EP - 60

BT - International Conference on Informatics and Systems, INFOS 2016

PB - Association for Computing Machinery (ACM)

T2 - 10th International Conference on Informatics and Systems, INFOS 2016

Y2 - 9 May 2016 through 11 May 2016

ER -

Hierarchical N-gram algorithm for extracting Arabic entities

Abstract

Conference

Keywords

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Cite this