A New Approach for Text Summarizer

Authors

  • Suman M Department of Electronics and Computer Engineering, K.L University, Vaddeswaram, Guntur
  • Maddu T
  • Shalini A
  • Bhavana K

Keywords:

Summarizer, Sentence Position, Sentence Resemblance, Lexical Similarity, coherence, redundancy

Abstract

Text Summarization is a process of giving the shorter version of a text document. For the research scholars who want to do research on a particular domain have to search a lot of documents. It is very difficult and it takes a lot of time to go through the domain, in this case there is a chance of missing some key word in those documents. To get rid of this problem it is better to have a summary of a document. Summarizer gives the summary of a paper. The summarizer can be developed using some algorithms like Sentence Position, Sentence resemblance to the title, Lexical Similarity etc. The main aim is to reduce the body of the text and maintaining coherence and avoiding redundancy.

References

I. Kupiec, J. Pedersen, and F. Chen, "A trainable document summarizer", In Proceedings of the 18th ACMSIGIR Conference, pages 68-73, 1995.

Lal, Partha. "Text Summarization.," (2002).

Goldstein, J. , Mittal, V. , Carbonell, J. , and Kantrowitz, M. (2000, April). Multi-document summarization by sentence extraction. In

Proceedings of the 2000 NAACL-ANLP Workshop on Automatic summarization-Volume 4 (pp. 40-48). Association for Computational Linguistics.

R. Ferreira, L. de Souza Cabral, R. D. Lins, G. P. e Silva, F. Freitas, G. D.Cavalcanti, R. Lima, S. J. Simske, and L. Favaro, “Assessing sentencescoring techniques for extractive text summarization,” Expert Systemswith Applications, vol. 40, no. 14, pp. 5755 5764, 2013.

YunFei Yi, Cheng Hua Li, Lijun Liu, Wei Song,Shuai Liu ”Machine Learning Algorithms with Co-occurrence based Term Association for Text Mining”

R. Ferreira, L. de Souza Cabral, R. D. Lins, G. P. e Silva, F. Freitas, G. D.Cavalcanti, R. Lima, S. J. Simske, and L. Favaro, “Assessing sentencescoring techniques for extractive text summarization,” Expert Systemswith Applications, vol. 40, no. 14, pp. 5755–5764, 2013.

A. Nenkova and R. Passonneau, "Evaluating Content Selection in Summarization: The Pyramid Method," In Proc. HLT/NAACL 2004.

J. Steinberger and J. Karel, "Evaluation Measures for Text Summarization," In Computing and Informatics, Vol. 28, pp. 1001–1026, Mar. 2009.

H. P. Edmundson, “New methods in automatic extracting,” J. ACM,vol. 16, no. 2, pp. 264–285, Apr. 1969.

E. Gamma, R. Helm, R. Johnson, and J. Vlissides, Design patterns:elements of reusable object-oriented software. Addison-Wesley

Professional,1995.

R. D. Lins, S. J. Simske, L. de Souza Cabral, G. de Silva, R. Lima, R. F. Mello, and L. Favaro, “A multi-tool scheme for summarizing textual documents,” in Proc. of 11st IADIS International Conference WWW/INTERNET 2012, July 2012, pp. 1–8.

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Published

2015-04-30

How to Cite

Suman, M., Maddu, T., Shalini, A., & Bhavana, K. (2015). A New Approach for Text Summarizer. COMPUSOFT: An International Journal of Advanced Computer Technology, 4(04), 1665–1669. Retrieved from https://ijact.in/index.php/j/article/view/293

Issue

Vol. 4 No. 04 (2015): April

Section

Review Article

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