CFP last date
20 January 2025
Call for Paper
February Edition
IJCA solicits high quality original research papers for the upcoming February edition of the journal. The last date of research paper submission is 20 January 2025

Submit your paper
Know more
The week's pick
Responsive image
SFLA-Based Line Balancing and Task Optimization in Master-Slave Controlled Hanger Transportation Systems for Garment Production

Duc Hoang Nguyen
Random Articles
Reseach Article

Text Template Mining using Named Entity Recognition

by Dania Sagheer, Fadel Sukkar
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 182 - Number 46
Year of Publication: 2019
Authors: Dania Sagheer, Fadel Sukkar
10.5120/ijca2019918622

Dania Sagheer, Fadel Sukkar . Text Template Mining using Named Entity Recognition. International Journal of Computer Applications. 182, 46 ( Mar 2019), 34-40. DOI=10.5120/ijca2019918622

@article{ 10.5120/ijca2019918622,
author = { Dania Sagheer, Fadel Sukkar },
title = { Text Template Mining using Named Entity Recognition },
journal = { International Journal of Computer Applications },
issue_date = { Mar 2019 },
volume = { 182 },
number = { 46 },
month = { Mar },
year = { 2019 },
issn = { 0975-8887 },
pages = { 34-40 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume182/number46/30463-2019918622/ },
doi = { 10.5120/ijca2019918622 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:14:27.075140+05:30
%A Dania Sagheer
%A Fadel Sukkar
%T Text Template Mining using Named Entity Recognition
%J International Journal of Computer Applications
%@ 0975-8887
%V 182
%N 46
%P 34-40
%D 2019
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper, the named entity recognition system is built using morphological, lexical and semantic analysis. Rule based system is designed for template mining from the Arabic text. Arabic texts are selected from oil production domain. They are taken from Arabic BBC, RT and CNN websites. The System is tested on these texts and the results give high performance, less error made and good accuracy in finding the templates from texts according to named entities extracted.

References
  1. Foley John., Sarwar M Sheikh., and Allan James., “Named Entity Recognition with Extremely Limited Data” arXiv:1806.04411v2 [cs.IR] 13 Jun 2018.
  2. Vargas-Vera Maria, Domingue John, Kalfoglou Yannis, Motta Enrico and Shum Buckingham Simon, “Template-Driven Information Extraction for Populating Ontologies”, Proceedings of the 2nd International Conference on Ontology Learning - Volume 38, Pages 35-40, Seattle, USA, 2001.
  3. Desai1 Prashant G., Sarojadevi H, Niranjan N. Chiplunkar, “A Template Based Algorithm for Automatic Summarization and Dialogue Management for Text Documents”, IJRET: International Journal of Research in Engineering and Technology, Volume: 04 Issue: 11 | Nov-2015
  4. Gobinda G. Chowdhury, “Template Mining for Information Extraction from Digtal Documents”, Division of Information Studies, School of Applied Science, Nanyang Technological, Nanyang Avenue, Singapore 639798 LIBRARY TRENDS, Vol. 48, No. I, Summer 1999, pp. 182-208.
  5. Onyshkevych Boyan, “Template Design for Information Extraction”, Proceedings of the 5th conference on Message understanding, 1993.
  6. Nathanael Chambers and Dan Jurafsky. Template-Based Information Extraction without the Templates, Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, 2011.
  7. Sagheer Dania, Sukkar Fadel, “A Template-Based Information Extraction System for Text Understanding”, International Journal of Computer Applications, Vol 182, NO 28, 2018.
  8. Biran, Or, Terra Blevins and Kathleen McKeown. “Mining Paraphrasal Typed Templates from a Plain Text Corpus.” ACL (2016).
  9. Raymond J. Mooney and Razvan Bunescu ,“Mining Knowledge from Text Using Information Extraction”, ACM SIGKDD Explorations Newsletter - Natural language processing and text mining, Volume 7 Issue 1, June 2005, Pages 3-10
  10. Girish Keshav Palshikar ,“Techniques for Named Entity Recognition: A Survey”, chapter 11, IGI Global, 2012.
  11. BOUDCHICHE Mohamed, MAZROUI Azzeddine, OULD Bebah Mohamed Ould Abdallahi, LAKHOUAJA Abdelhak, BOUDLAL Abderrahim. AlKhalil Morpho Sys 2: A robust Arabic morpho-syntactic analyzer, Journal of King Saud University – Computer and Information Sciences, 2017, 141–146p.
  12. The Stanford Natural Language Processing Group: https://nlp.stanford.edu/software/tagger.shtml, Access Date 1/1/2018.
  13. Arramooz AlWaseet: Arabic dictionary for morphology: http://arramooz.sourceforge.net. Access Date 1/1/2018.
Index Terms

Computer Science
Information Sciences

Keywords

Named Entity Recognition Template Mining Morphological Analysis Lexicon Semantic Analysis.

Powered by PhDFocusTM