التلخيص التلقائي للنصوص العربية
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منشور:
Dec 28, 2013
الكلمات المفتاحية:
التلخيص الآلي، النظام المعرفي، المعرفة اللغوية، النمط اللغوي، التسميات الدلالية، خوارزمية المطابقة.
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الملخص
تقدم هذه الورقة ملخصًا آليًا للنصوص العربية. الهدف الرئيسي للملخص هو إنتاج نسخة مختصرة من محتوى نص الإدخال لمختلف المستخدمين. يستغل هذا المنهج بشكل رئيسي تعابير اللغة الموجودة في النص والتي تدل على أهمية الجمل وفقا لوجهة نظر المؤلف بغض النظر عن المجال. يختار الملخص الجمل الأكثر صلة بناءً على المعرفة اللغوية في شكل أنماط لغوية تمثل تعبيرات اللغة وقوائم الكلمات. التعبيرات اللغوية تعبر عن المعرفة اللغوية وهي مستقلة عن أي مجال محدد. تعرض الورقة عملية الاكتساب اللغوي التي تغذي قاعدة المعرفة اللغوية، وبنية النظام بما في ذلك ثلاث وحدات، وتنفيذ النظام.
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كيفية الاقتباس
بيريج., & hgytvdع. (2013). التلخيص التلقائي للنصوص العربية. AL-Lisaniyyat, 19(2), 22-32. https://doi.org/10.61850/allj.v19i2.481
القسم
Articles
المراجع
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[2] Berri J, Le Roux. D, Malrieu, D, Minel, J.-L., “SERAPHIN main sentences
automatic extraction system”, proceedings of the Second Language Engineering
Convention, London, UK, 1995.
[3] J. Berri, Contribution to the contextual exploration method. Applications to automatic
abstracting and to temporal representations. Implementation of SERAPHIN system.…
Ph.D. thesis, Paris-Sorbonne University (Paris V), France, 1996. (French publication)
[4] H. P. Luhn, “The automatic creation of literature abstracts”. /BM journal for research
and development, 2, 159-165, 1958,
[5] I Mani, Automatic summarization, John Benjamins Publishing Company.
Amsterdam, 2001.
[6] W. Kinsh, T. A. Van Dijk, “Toward a model of text comprehension and production”,
Psychological review, 85, 363-394, 1978.
[7] G. F. DeJong, *An overview of FRUMP system”, Strategies for natural language
processing, Lehnert and Ringle ed., Hillsdale, NJ: Erlbaum Ass., 149-172, 1982.
[8] R. Alterman and L. Bookman, “Some Computational Experiments in
Summarization”, Discourse Processes, 13, 143-174, 1990.
[9] G. Kallgreen, “Automatic abstracting of content in text”, Nordic journal of linguistics,
11,89-110, 1988.
[10] G. SALTON, Automatic Text Processing. The transformation. analysis, and
retrieval of information computer, Addison-Wesley, New York, 1989.
[11] P. Schäuble, “SPIDER : a multiuser information retrieval system for semistructured
and dynamic data”, ACM SIGIR conference on R&D in information retrieval, 318-327,
1993.
[12] S. Miike, E. Itoh, K. Ono, K. Sumita, “A full-text retrieval system with a dynamic
abstract generation function”, Proceedings SIGIR'94, ed. W. Bruce Croft and C. J. van
Rijsbergen, Springer-Verlag, Dublin, 152-161, 1994,
[13] D. Mareu, “Discourse trees are good indicators of importance in texts”, advances in
Automatic Text Summarization, Ed. Inderjeet Mani and Mark T. Maybury, MIT press,
USA, 123-136, 1999.
[14]C. D. Paice, “Constructing literature abstracts by computer: techniques and
prospects”. Information processing management, 26 (1), 171-186, 1990.
[15] Kim, J.-T.. Moldovan I.: “Acquisition of Linguistic Patterns for Knowledge-Based
Information Extraction” /EEE Transactions on Knowledge and Data Engineering, Vol. 7,
No. 5, 713-724, Oct. 1995.
[16] Mädche, A., Neumann, G. Staab S.: 1999. *A Generic Architectural Framework for
Text Knowledge Acquisition”, Unpublished Technical Report, Kalsruhe University, 18p,
1999. Available at htip: www.aifb.uni-kalsruhe.de WBS
[17] J. Berri, M. Al-Khamis, “Information Exploration Using Mobile Agents”, WSEAS
Transactions on Computers, 3 (3), 706-712, 2004.