CFP last date
15 May 2024
Call for Paper
June Edition
IJAIS solicits high quality original research papers for the upcoming June edition of the journal. The last date of research paper submission is 15 May 2024

Submit your paper
Know more
The week's pick
Responsive image
Analysis of ANN Training Algorithms for Hand Geometry-Based Access Control

Kazeem B. Adedeji Apena Waliu O. Adu Michael R.
Random Articles
Reseach Article

An Approach for Concept-based Automatic Multi-Document Summarization using Machine Learning

by G. Padmapriya, K. Duraiswamy
journal cover thumbnail

International Journal of Applied Information Systems
Foundation of Computer Science (FCS), NY, USA
Volume 3 - Number 3
Year of Publication: 2012
Authors: G. Padmapriya, K. Duraiswamy
http:/ijais12-450491

G. Padmapriya, K. Duraiswamy . An Approach for Concept-based Automatic Multi-Document Summarization using Machine Learning. International Journal of Applied Information Systems. 3, 3 ( July 2012), 49-53. DOI=http:/ijais12-450491

@article{ http:/ijais12-450491,
author = { G. Padmapriya, K. Duraiswamy },
title = { An Approach for Concept-based Automatic Multi-Document Summarization using Machine Learning },
journal = { International Journal of Applied Information Systems },
issue_date = { July 2012 },
volume = { 3 },
number = { 3 },
month = { July },
year = { 2012 },
issn = { 2249-0868 },
pages = { 49-53 },
numpages = {9},
url = { https://www.ijais.org/archives/volume3/number3/215-0491/ },
doi = { http:/ijais12-450491 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2023-07-05T10:45:23.449662+05:30
%A G. Padmapriya
%A K. Duraiswamy
%T An Approach for Concept-based Automatic Multi-Document Summarization using Machine Learning
%J International Journal of Applied Information Systems
%@ 2249-0868
%V 3
%N 3
%P 49-53
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Text Summarization is compressing the source text into a shorter version preserving its information content and overall meaning. It is very complicated for human beings to manually summarize large documents of text. Text summarization plays an important role in the area of natural language processing and text mining. Many approaches use statistics and machine learning techniques to extract sentences from documents. This paper presents an new approach for concept-based automatic multi-document summarization using machine learning.

References
  1. Gobinda G. Chowdhury, "Natural Language Processing", Annual Review of Information Science and Technology, Vol: 37, pp: 51–89, 2003.
  2. E D Liddy, "Natural Language Processing", In Encyclopedia of Library and Information Science, 2nd Edition, 2001.
  3. Inderjeet Mani, "Recent Developments in Text Summarization", In Proceedings of the tenth international conference on Information and knowledge management, ACM Press, pp: 529 - 531, 2001.
  4. Kaustubh Patil and Pavel Brazdil, "Sumgraph: Text Summarization Using Centrality in the Pathfinder Network", In IADIS International Journal on Computer Science and Information Systems, Vol. 2, No. 1, pp: 18-32, 2007.
  5. Dou Shen, Jian-Tao Sun, Hua Li, Qiang Yang and Zheng Chen, "Document Summarization using Conditional Random Fields", In Proceedings of IJCAI, 2007.
  6. Dragomir R. Radev, Eduard Hovy, Kathleen McKeown, "Introduction to the Special Issue on Summarization", In Computational Linguistics, Vol: 28, Issue 4, pp: 402, 2002.
  7. Jen-Yuan Yeh, Hao-Ren Ke and Wei-Pang Yanget, "iSpreadRank: Ranking sentences for extraction-based summarization using feature weight propagation in the sentence similarity network", Expert Systems with Applications, Vol: 35, pp: 1452, 2008.
  8. Dragomir R. Radev a, Hongyan Jing, Magorzata Sty and Daniel Tam, "Centroid-based summarization of multiple documents", Information Processing and Management, vol. 40, no. 6, pp. 919–938, 2004.
  9. Florian Boudin and Juan Manuel Torres Moreno, " NEO-CORTEX: A Performant User-Oriented Multi-Document Summarization System", Lecture Notes in Computer Science", Springer, Vol 4394, pp. 551-562, May 2007.
  10. Fu Lee Wang, Christopher C. Yang and Xiaodong Shi," Multi-document Summarization for Terrorism Information Extraction", Lecture Notes in Computer Science", Springer, vol. 3975, May 2006.
  11. Aaron Harnly, Ani Nenkova, Rebecca Passonneau and Owen Rambow, "Automation of Summary Evaluation by the Pyramid Method", In Proceedings of the Conference of Recent Advances in Natural Language Processing, pp: 226, 2005.
  12. Rachit Arora and Balaraman Ravindran, "Latent Dirichlet Allocation Based Multi-Document Summarization", In Proceedings of the second workshop on Analytics for noisy unstructured text data, pp:91-97, 2008.
  13. J. Goldstein, V. Mittal, J. Carbonell, and M. Kantrowitz, "Multi-document summarization by sentence extraction", ANLP/NAACL Workshop, pp: 40–48, 2000.
  14. E. Hovy and C. Lin. , "Automated text summarization in SUMMARIST", In Advances in Automatic Text Summarization, 1999.
  15. James Allan, Rahul Gupta, and Vikas Khandelwal, "Temporal Summaries of News Topics", 2001.
  16. Yan Liu, Sheng-hua Zhong, Wen-jie Li, "Query-oriented Unsupervised Multi-document Summarization via Deep Learning", Under review in Journal of Neural Networks (NN).
  17. Liangda Li, Ke Zhou, Gui-Rong Xue, Hongyuan Zha, Yong Yu, "Enhancing Diversity, Coverage and Balance for Summarization through Structure Learning", In www 2009 madrid, pp: 71-72, 2009.
  18. L. H. Chong, and Y. Y. Chen, "Text Summarization for Oil and Gas News Article", 2009.
  19. H. Gregory Silber, Kathleen F. McCoy, "Efficiently Computed Lexical Chains as an Intermediate Representation for Automatic Text Summarization", Association for Computational Linguistics, Vol: 28, 2002.
  20. McKeown, K. R. , Klavans, J. L. , Hatzivassiloglou, V. , Barzilay, R. , Eskin, E. , "Towards multi-document summarization by reformulation: Progreess and prospects", In Proceedings of the Sixteenth National Conference on Artificial Intelligence, pp: 293, 1999.
  21. Yllias Chali, "Generic and Query-Based Text Summarization Using Lexical Cohesion", Proceedings of the 15th Conference of the Canadian Society for Computational Studies of Intelligence on Advances in Artificial Intelligence, Springer-Verlag London, pp: 293-302, 2002.
  22. Khosrow Kaikhah, "Automatic Text Summarization with Neural Networks", Second IEEE International conference on intelligent systems, pp: 40-45, 2004.
  23. M. S. Binwahlan, N. Salim, L. Suanmali, "Intelligent Model for Automatic Text Summarization", Information Technology Journal, pp: 1249-1255, 2009.
  24. H. Luhn, "The automatic creation of literature abstracts", IBM Journal of Research and Development, Vol: 2, Number: 2, pp: 159-165, 1958.
  25. H. Edmundson, "New methods in automatic extracting", Journal of the Association for Computing Machinery, Vol: 16, No. 2, pp: 264-285, 1969.
  26. Hassel M. , "Resource Lean and Portable Automatic Text Summarization", PhD thesis, School of Computer Science and Communication, 2007.
  27. Michel Gagnon, Lyne Da Sylva, "Text Summarization by Sentence Extraction and Syntactic Pruning", In Proceedings of Computational Linguistics in the North East, 2005.
  28. Kevin Knight, Daniel Marcu, "Summarization beyond sentence extraction:A probabilistic approach to sentence compression", In Artificial Intelligence, Vol: 139, Issue 1, pp: 91–107, 2002.
  29. I. Mani, M. Maybury, "Advances in Automatic Text Summarization", MIT Press, 1999.
  30. H Jing, K McKeown, "The decomposition of human-written summary sentences", In 22nd International Conference on Research and Development in Information Retrieval, pp: 129-136, 1999.
  31. Breck Baldwin and Thomas S. Morton, "Dynamic coreference-based summarization", in Proceedings of the Third Conference on Empirical Methods in Natural Language Processing (EMNLP-3), Granada, Spain, June 1998.
  32. Shasha Xie, Yang Liu, "Improving supervised learning for meeting summarization using sampling and regression", In Computer Speech and Language, Vol: 24, Issue 3, 2009.
  33. Allan Borra, Almira Mae Diola, Joan Tiffany T. Ong Lopez, Phoebus Ferdiel Torralba, Sherwin So, "Using Rhetorical Structure Theory in Automatic Text Summarization for Marcu-Authored Documents", In titaniaaddueduph, 2010.
  34. Rafeeq Al-Hashemi, "Text Summarization Extraction System (TSES)Using Extracted Keywords", International Arab Journal of e-Technology, Vol. 1, No. 4, pp: 164-168, 2010.
  35. Gianluca Demartini, Malik Muhammad Saad Missen, Hugo Zaragoza, "Entity Summarization of News Articles", In SIGIR, pp: 795-796, 2010.
  36. Liang Zhou, Miruna Ticrea and Eduard Hovy, "Multi-document Biography Summarization", in Proceedings of Empirical Methods in Natural Language Processing, 2004.
  37. Shiyan Ou, Christopher S. G. Khoo and Dion H. Goh, "Design and development of a concept-based multidocument summarization system for research abstracts", Journal of Information Science, vol. 34 , no. 3, pp. 308-326 , June 2008.
  38. You Ouyang, Wenji Li and Qin Lu, "An Integrated Multi-document Summarization Approach based on Word Hierarchical Representation", in proceedings of the ACL-IJCNLP, singapore, pp. 109–112, 2009.
  39. Mohammed Salem Binwahlan, Naomie Salim and Ladda Suanmali, "Swarm Based Features Selection for Text Summarization", IJCSNS International Journal of Computer Science and Network Security, vol. 9, no. 1, January 2009.
Index Terms

Computer Science
Information Sciences

Keywords

Multi-document Summarization Machine Learning

Powered by PhDFocusTM