A brief review on text summarization methods

 
 
 
  • Abstract
  • Keywords
  • References
  • PDF
  • Abstract


    In present scenario, text summarization is a popular and active field of research in both the Information Retrieval (IR) and Natural Language Processing (NLP) communities. Summarization is important for IR since it is a means to identify useful information by condensing the document from large corpus of data in an efficient way. In this study, different aspects of text summarization methods with strength, limitation and gap within the methods are presented.

     

     

     

  • Keywords


    Summarization Steps; Methods; Summary.

  • References


      [1] Gholamrezazadeh S, Salehi MA, Gholamzadeh B. A comprehensive survey on text summarization systems. Computer Science and its Applications. 2009 Dec, 10, pp. 1-6.

      [2] Hovy E, Lin CY. Automated Text Summarization and the Summarist System, TIPSTER III Final Report (SUMMAC). 1998, pp. 197-214.

      [3] Hovy E, Lin CY. Automated text summarization in SUMMARIST. MIT Press.1999, pp. 81–94.

      [4] Hovy E, Lin C Y, Marcu D. Automated Text Summarization, SIGIR'99 Tutorial, Berkeley, CA, Tutorial: Automated. 1999.

      [5] Lloret E, Palomar M. Text summarisation in progress: a literature review. 2012, 37, pp. 1-41.

      [6] Partha L. Text summarization,June 13, 2002.

      [7] Patil S R, Mahajan S R. Domain Specific e-Document Summarization Using Extractive Approach. IJCA Proceedings on International Conference and workshop on Emerging Trends in Technology (ICWET). 2011, 11, pp. 36-41.

      [8] Luhn, H. P. (1958). The automatic creation of literature abstracts. IBM Journal of research and development. 2(2), 159-65.

      [9] Wan, X., Yang, J., & Xiao, J. (2007). Towards a unified approach based on affinity graph to various multi-document summarizations. In: Proceedings of the 11th European conference, 297–308.

      [10] Fellbaum, C. (1998).WordNet: an electronical lexical database. The MIT Press, Cambridge.

      [11] Kamyar, H., Kahani, M., Kamyar, M., & Poormasoomi, A. (2011). An Automatic Linguistics Approach for Persian Document Summarization. InAsian Language Processing (IALP). 2011 International IEEE Conference. 141-44.

      [12] Lin, C.Y., & Hovy, E. (2000). The Automated Acquision of topic signatures for text summarization. Proceeding COLING '00 Proceedings of the 18th conference on Computational linguistic. 1, 495-501.

      [13] Li, S., Ouyang, Y., Wang, W., & Sun, B.(2007). Multi-document summarization using support vector regression. In: The document understanding workshop (presented at the HLT/NAACL). Rochester. New York USA.

      [14] Priya, G. P, & Duraiswamy, K. (2012). An approach for concept-based automatic multi-document summarization using machine learning.International Journal of Applied Information Systems (IJAIS). 3(3), 49-53.

      [15] Zamanifar, A., Minaei-Bidgoli, B., & Sharifi, M. (2008). A New Hybrid Farsi Text Summarization Technique Based on Term Co-Occurrence and Conceptual Property of Text. In Proceedings of Ninth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing. IEEE. Washington, DC, USA, 635-639.

      [16] Wang, M., Wang, X., & Xu, C. (2005). An Approach to Concept Oriented Text Summarization. In Proceedings of ISCIT’05. IEEE international conference, China. 1290-1293.

      [17] Suanmali, L., Binwahlan, S. M., & Salim, N.(2009) Sentence features fusion for text summarization using fuzzy logic. Hybrid Intelligent Systems, 2009. HIS'09. Ninth International Conference on.IEEE, 1.

      [18] Das, D., & Martins, A.F. (2007). A survey on automatic text summarization. Literature Survey for the Language and Statistics II course at CMU. 4, 192-5.


 

View

Download

Article ID: 25070
 
DOI: 10.14419/ijet.v7i4.5.25070




Copyright © 2012-2015 Science Publishing Corporation Inc. All rights reserved.