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Exploring clustering for multi-document Arabic summarisation

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Exploring clustering for multi-document Arabic summarisation. / El-Haj, Mahmoud; Kruschwitz, Udo; Fox, Chris.

Information Retrieval Technology: 7th Asia Information Retrieval Societies Conference, AIRS 2011, Dubai, United Arab Emirates, December 18-20, 2011. Proceedings. ed. / Mohamed Vall Mohamed Salem; Khaled Shaalan; Farhad Oroumchian; Azadeh Shakery; Halim Khelalfa. Berlin : Springer, 2011. p. 550-561 (Lecture Notes in Computer Science; Vol. 7097).

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

Harvard

El-Haj, M, Kruschwitz, U & Fox, C 2011, Exploring clustering for multi-document Arabic summarisation. in MVM Salem, K Shaalan, F Oroumchian, A Shakery & H Khelalfa (eds), Information Retrieval Technology: 7th Asia Information Retrieval Societies Conference, AIRS 2011, Dubai, United Arab Emirates, December 18-20, 2011. Proceedings. Lecture Notes in Computer Science, vol. 7097, Springer, Berlin, pp. 550-561. https://doi.org/10.1007/978-3-642-25631-8_50

APA

El-Haj, M., Kruschwitz, U., & Fox, C. (2011). Exploring clustering for multi-document Arabic summarisation. In M. V. M. Salem, K. Shaalan, F. Oroumchian, A. Shakery, & H. Khelalfa (Eds.), Information Retrieval Technology: 7th Asia Information Retrieval Societies Conference, AIRS 2011, Dubai, United Arab Emirates, December 18-20, 2011. Proceedings (pp. 550-561). (Lecture Notes in Computer Science; Vol. 7097). Springer. https://doi.org/10.1007/978-3-642-25631-8_50

Vancouver

El-Haj M, Kruschwitz U, Fox C. Exploring clustering for multi-document Arabic summarisation. In Salem MVM, Shaalan K, Oroumchian F, Shakery A, Khelalfa H, editors, Information Retrieval Technology: 7th Asia Information Retrieval Societies Conference, AIRS 2011, Dubai, United Arab Emirates, December 18-20, 2011. Proceedings. Berlin: Springer. 2011. p. 550-561. (Lecture Notes in Computer Science). https://doi.org/10.1007/978-3-642-25631-8_50

Author

El-Haj, Mahmoud ; Kruschwitz, Udo ; Fox, Chris. / Exploring clustering for multi-document Arabic summarisation. Information Retrieval Technology: 7th Asia Information Retrieval Societies Conference, AIRS 2011, Dubai, United Arab Emirates, December 18-20, 2011. Proceedings. editor / Mohamed Vall Mohamed Salem ; Khaled Shaalan ; Farhad Oroumchian ; Azadeh Shakery ; Halim Khelalfa. Berlin : Springer, 2011. pp. 550-561 (Lecture Notes in Computer Science).

Bibtex

@inproceedings{d8450bd631f444b2a6a6912a85f9ae4e,
title = "Exploring clustering for multi-document Arabic summarisation",
abstract = "In this paper we explore clustering for multi-document Arabic summarisation. For our evaluation we use an Arabic version of the DUC-2002 dataset that we previously generated using Google Translate. We explore how clustering (at the sentence level) can be applied to multi-document summarisation as well as for redundancy elimination within this process. We use different parameter settings including the cluster size and the selection model applied in the extractive summarisation process. The automatically generated summaries are evaluated using the ROUGE metric, as well as precision and recall. The results we achieve are compared with the top five systems in the DUC-2002 multi-document summarisation task.",
author = "Mahmoud El-Haj and Udo Kruschwitz and Chris Fox",
year = "2011",
doi = "10.1007/978-3-642-25631-8_50",
language = "English",
isbn = "9783642256301",
series = "Lecture Notes in Computer Science",
publisher = "Springer",
pages = "550--561",
editor = "Salem, {Mohamed Vall Mohamed} and Khaled Shaalan and Farhad Oroumchian and Azadeh Shakery and Halim Khelalfa",
booktitle = "Information Retrieval Technology",

}

RIS

TY - GEN

T1 - Exploring clustering for multi-document Arabic summarisation

AU - El-Haj, Mahmoud

AU - Kruschwitz, Udo

AU - Fox, Chris

PY - 2011

Y1 - 2011

N2 - In this paper we explore clustering for multi-document Arabic summarisation. For our evaluation we use an Arabic version of the DUC-2002 dataset that we previously generated using Google Translate. We explore how clustering (at the sentence level) can be applied to multi-document summarisation as well as for redundancy elimination within this process. We use different parameter settings including the cluster size and the selection model applied in the extractive summarisation process. The automatically generated summaries are evaluated using the ROUGE metric, as well as precision and recall. The results we achieve are compared with the top five systems in the DUC-2002 multi-document summarisation task.

AB - In this paper we explore clustering for multi-document Arabic summarisation. For our evaluation we use an Arabic version of the DUC-2002 dataset that we previously generated using Google Translate. We explore how clustering (at the sentence level) can be applied to multi-document summarisation as well as for redundancy elimination within this process. We use different parameter settings including the cluster size and the selection model applied in the extractive summarisation process. The automatically generated summaries are evaluated using the ROUGE metric, as well as precision and recall. The results we achieve are compared with the top five systems in the DUC-2002 multi-document summarisation task.

U2 - 10.1007/978-3-642-25631-8_50

DO - 10.1007/978-3-642-25631-8_50

M3 - Conference contribution/Paper

SN - 9783642256301

T3 - Lecture Notes in Computer Science

SP - 550

EP - 561

BT - Information Retrieval Technology

A2 - Salem, Mohamed Vall Mohamed

A2 - Shaalan, Khaled

A2 - Oroumchian, Farhad

A2 - Shakery, Azadeh

A2 - Khelalfa, Halim

PB - Springer

CY - Berlin

ER -