Abstract
In the era of data overloading, Text Summarization systems (TSs) is one of the important Natural Language processing applications. These systems provide a concise form for the input document(s). According to the type of output summary, Text Summarization can be classified into extractive and abstractive. While the extractive text summarization is the process of identifying the important sections of the input text and producing them verbatim, the abstractive text summarization produces a new material in a generalized form. To facilitate the topic-oriented summarization, current research efforts focus on query-based text summarization, which summarizes the input document according to the user query. Although, the Arabic language is one of the Semitic languages and is spoken by 422 million people, there are very limited research efforts in Arabic query-based text summarization. In this paper, we propose a new Arabic query-based text summarization model. The model accepts both user query and Arabic document and then generates the extractive summary. The proposed model generates the extractive summary for the input document semantically by applying the Latent Semantic Analysis technique and exploiting the Arabic WordNet (AWN) ontology. Finally, to show the importance of the proposed model, a case study is presented.
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References
Alamin, N., Meknassi, M., Rais, N.: Automatic texts summarization: current state of the art. J. Asian Sci. Res. 5(1), 1–15 (2015)
Azmi, A., Al-thanyyan, S.: Ikhtasir—a user selected compression ratio Arabic text summarization system. In: International Conference on Natural Language Processing and Knowledge Engineering, Dalian, China, 24–27 September 2009, pp. 1–7 (2009)
Badry, R., Sharaf Eldin, A., Elzanfally, D.: Text summarization within the latent semantic analysis framework: comparative study. Int. J. Comput. Appl. (IJCA) 81(11), 40–45 (2013a)
Badry, R., Sharaf Eldin, A., Elzanfally, D.: Text summarization of arabic and english texts. In: Proceedings of the Sixth International Conference on Intelligent Computing and Information Systems (ICICIS), Cairo, Egypt, 14–16 December 2013, pp. 123–129 (2013b)
Black, W., Elkateb, S., Vossen, P.: Introducing the Arabic WordNet project. In: Third International WordNet Conference (GWC-06), Korea (2006)
Das, D., Martins, A.: A survey on automatic text summarization. Technical report, Carnegie Mellon University, US, November 2007
El-Haj, M., Hammo, B.: Evaluation of query-based arabic text summarization system. In IEEE Proceeding of the NLP-KE 2008, Beijing, China, 19–22 October 2008 (2008)
El-Haj, M., Kruschwitzand, U., Fox, C.: Experimenting with automatic text summarisation for arabic. In: Human Language Technology: LTC 2009. Lecture Notes in Computer Science, vol. 6562, pp. 490–499. Springer, Heidelberg (2011)
Gholamrezazadeh, S., Salehi, M., Gholamzadeh, B.: Comprehensive survey on text summarization systems. In: 2nd International Conference on Computer Science and its Applications, Jeju, Korea, pp. 1–6 (2009)
Gupta, V., Lehal, G.S.: A survey of text summarization extractive techniques. J. Emerg. Technol. Web Intell. 2(3), 258–268 (2010)
Hovy, E., Lin, C.: Automated text summarization in SUMMARIST. In: Mani, I., Maybury, M. (eds.) Advances in Automated Text Summarization, pp. 81–94. MIT Press, Cambridge (1999)
Imam, I., Hamouda, A., Abdul Khalek, H.: An ontology-based summarization system for arabic documents (OSSAD). Int. Conf. Comput. Appl. 74(17), 38–43 (2013)
Khoja, S., Garside, R.: Stemming arabic text. Computing Department, Lancaster University, Lancaster (1999). http://www.comp.lanc.ac.uk/computing/users/khoja/stemmer.ps
Krishna, R.V.V.M., Kumar, S.V.P., Reddy, C.S.: A hybrid method for query based automatic summarization system. Int. J. Comput. Appl. 68(6), 39–43 (2013)
Leuva, S.: A Survey on A hybrid method for query based automatic summarization system for text. In: International Institution for Technological Research and Development, vol. 1, no. 3 (2016)
Moawad, I., Aref, M.: Semantic graph reduction approach for abstractive text summarization. In: 2012 Seventh International Conference on Computer Engineering & Systems (ICCES), 2012, pp. 132–138 (2012)
Ozsoy, M.G.: Text summarization using latent semantic analysis. Masters thesis, Department of Computer Engineering, Middle East Technical University, Turkey (2011)
Ozsoy, M.G., Cicekliand, I., Alpaslan, F.: Text summarization of Turkish texts using latent semantic analysis. In: Proceedings of the 23rd International Conference on Computational Linguistics (Coling 2010), pp. 869–876 (2010)
Radev, D.R., McKeown, K.: Introduction to the special issue on summarization. Comput. Linguist. – Summarization 28(4), 399–408 (2002)
Rahman, N., Borah, B.: A survey on existing extractive techniques for query-based text summarization. In: International Symposium on Advanced Computing and Communication (ISACC) (2015)
Yang, G.: A novel contextual topic model for query-focused multi-document summarization. In: Proceedings of IEEE 26th International Conference on Tools with Artificial Intelligence, pp. 576–583 (2014)
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Badry, R.M., Moawad, I.F. (2020). A Semantic Text Summarization Model for Arabic Topic-Oriented. In: Hassanien, A., Azar, A., Gaber, T., Bhatnagar, R., F. Tolba, M. (eds) The International Conference on Advanced Machine Learning Technologies and Applications (AMLTA2019). AMLTA 2019. Advances in Intelligent Systems and Computing, vol 921. Springer, Cham. https://doi.org/10.1007/978-3-030-14118-9_52
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DOI: https://doi.org/10.1007/978-3-030-14118-9_52
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