CFP last date
20 December 2024
Reseach Article

A Hybrid Method for Query based Automatic Summarization System

by R. V. V. Murali Krishna, S. Y. Pavan Kumar, Ch. Satyananda Reddy
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 68 - Number 6
Year of Publication: 2013
Authors: R. V. V. Murali Krishna, S. Y. Pavan Kumar, Ch. Satyananda Reddy
10.5120/11587-6925

R. V. V. Murali Krishna, S. Y. Pavan Kumar, Ch. Satyananda Reddy . A Hybrid Method for Query based Automatic Summarization System. International Journal of Computer Applications. 68, 6 ( April 2013), 39-43. DOI=10.5120/11587-6925

@article{ 10.5120/11587-6925,
author = { R. V. V. Murali Krishna, S. Y. Pavan Kumar, Ch. Satyananda Reddy },
title = { A Hybrid Method for Query based Automatic Summarization System },
journal = { International Journal of Computer Applications },
issue_date = { April 2013 },
volume = { 68 },
number = { 6 },
month = { April },
year = { 2013 },
issn = { 0975-8887 },
pages = { 39-43 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume68/number6/11587-6925/ },
doi = { 10.5120/11587-6925 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:27:08.874600+05:30
%A R. V. V. Murali Krishna
%A S. Y. Pavan Kumar
%A Ch. Satyananda Reddy
%T A Hybrid Method for Query based Automatic Summarization System
%J International Journal of Computer Applications
%@ 0975-8887
%V 68
%N 6
%P 39-43
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Automatic text summarization is one of the research goals of Natural Language Processing which relieves humans from studying each and every line in a text document to understand the underlying concepts in it. Automatic text summarization is aimed to create a brief outline of a given text covering the important points in the text. Automatic text summarization can be generic or query specific. This paper is focused on Query specific text summarization where a summary of the given text is constructed based on the given query. Query specific text summarization is based on the calculation of the relationship between sentences in the text document and the query given. Several statistical techniques and linguistic techniques have been developed to find the relationship between the given query and the sentences in the document. These methods when used alone could not give desired accuracy in the results. In this paper a sentence scoring method is defined based on existing sentence scoring methods. It attempts to combine the individual results of these methods to give a better assessment of the relationship between the sentences.

References
  1. Gholamrezazadeh, Saeedeh; Salehi, Mohsen Amini; Gholamzadeh, Bahareh, "A Comprehensive Survey on Text Summarization Systems," Computer Science and its Applications, 2009. CSA '09. 2nd International Conference on , vol. , no. , pp. 1,6, 10-12 Dec. 2009 doi: 10. 1109/CSA. 2009. 5404226
  2. YoungkoongKo, JungyunSeo, "An Effective Sentence-Extraction Technique Using Contextual Information and Statistical Approaches for Text Summarization", Pattern Recognition Letters. doi:10. 1016/j. patrec. 2008. 02. 008
  3. Wasson, M. , "Using leading text for news summaries: Evaluation results and implications for commercial summarization applications", in Proc. 17th International Conference on Computational Linguistics and 36th Annual Meeting of the ACL, 1998, pp. 1364-1368
  4. Salton, G, Automatic Text Processing: The Transformation, Analysis, and Retrieval of Information by Computer, Addison-Wesley Publishing Company, 1989.
  5. Waleed al-sanie, "Towards an infrastructure for Arabic text summarization using rhetorical structure theory", Master Thesis, Department of computer science. King Saud University, Riyadh, Kingdom of Saudi Arabia, 2005.
  6. http://web. science. mq. edu. au/~swan/summarization/projects_full. htm
  7. Bellegarda, J. , "Exploiting latent semantic information in statistical language modeling," in Proc. IEEE, August 2000. Vol. 88, No. 8,pp: 1279-1296.
  8. R. L. Cilibrasi and P. M. B. Vitanyi, "The google similarity distance," IEEE Trans. On Knowl. and Data Eng. , vol. 19, no. 3, pp. 370–383, 2007.
  9. Zhang Pei-ying and LI un-he,"Automatic text summarization based on sentences clustering and extraction" , IEEE2009
  10. Yuhua Li, Zuhair Bandar, David McLean and James O'Shea ,"A Method for Measuring Sentence Similarity and its application to conversational agents"
  11. Harish Karnick and VaruneshMishra,"Query Specific Multi-Document Summarization", Indian Institute of Technology, Kanpur, April 25, 2010
  12. Adamson, G and J. Boreham, " The use of an Association Measure Based on Character Structure to identify semantically related pairs ofwords and document titles".
Index Terms

Computer Science
Information Sciences

Keywords

Automatic text summarization Natural language processing statistical techniques linguistic techniques stemming n-gram clustering