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

Domain Specific Named Entity Recognition (DSNER) from Web Documents

by Pawan Kumar, Raj Kumar Goel, Prem Sagar Sharma
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 86 - Number 18
Year of Publication: 2014
Authors: Pawan Kumar, Raj Kumar Goel, Prem Sagar Sharma
10.5120/15087-3360

Pawan Kumar, Raj Kumar Goel, Prem Sagar Sharma . Domain Specific Named Entity Recognition (DSNER) from Web Documents. International Journal of Computer Applications. 86, 18 ( January 2014), 24-29. DOI=10.5120/15087-3360

@article{ 10.5120/15087-3360,
author = { Pawan Kumar, Raj Kumar Goel, Prem Sagar Sharma },
title = { Domain Specific Named Entity Recognition (DSNER) from Web Documents },
journal = { International Journal of Computer Applications },
issue_date = { January 2014 },
volume = { 86 },
number = { 18 },
month = { January },
year = { 2014 },
issn = { 0975-8887 },
pages = { 24-29 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume86/number18/15087-3360/ },
doi = { 10.5120/15087-3360 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:04:34.599970+05:30
%A Pawan Kumar
%A Raj Kumar Goel
%A Prem Sagar Sharma
%T Domain Specific Named Entity Recognition (DSNER) from Web Documents
%J International Journal of Computer Applications
%@ 0975-8887
%V 86
%N 18
%P 24-29
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Named entity recognition is a tool, which use process natural language tasks such as, text categorization, speech translation, and document classification. The Web data promotes the idea, that more and more data can be interconnected. A step towards this goal is to bring more structured annotations to existing documents using common vocabularies or ontology. Semi-structured texts such as scientific, medical, forum and blog posts can hence be semantically annotated. Named Entity (NE) extractors play a key role for extracting structured information by identifying features, also called entities, and by linking them to other web resources by means of typed inferences. Earlier many systems have been developed named entity recognition with substantial success save for the problem of being domain specific and making it difficult to use the different systems across domains. In this paper we introduce specific domain like science, medical and news, named entity recognition. This paper presents a system to recognize the Named Entity from web documents using ontology.

References
  1. Michailidis, Konstantinos Diamantaras & SpirosVasileiadis "Greek Named Entity Recognition using Support Vector Machines", Proceedings of the 7th International Conference on Greek Linguistics
  2. N. Chinchor, "MUC-6 Named Entity Task Definition (version 2. 1)", in Proceedings of the 6th Message Understanding Conference (MUC-6), Morgan-Kaufmann, Columbia, Maryland, November 1995.
  3. N. Chinchor, "MUC-7 Named Entity Task Definition (version 3. 5)", in Proceedings of the 7th Message Understanding Conference (MUC-7), Fairfax, VA, 19 April - 1 May 1998.
  4. N. Friburger and D. Maurel, "Textual similarity based on Proper Names", in Proceedings of the workshop Mathematical / Formal methods in Information Retrieval (MFIR '2002) at the 25th ACM SIGIR Conference, Tampere, Finland, 2002, pp. 155-167.
  5. N. Friburger and D. Maurel, "Textual similarity based on Proper Names", in Proceedings of the workshop Mathematical / Formal methods in Information Retrieval (MFIR '2002) at the 25th ACM SIGIR Conference, Tampere, Finland, 2002, pp. 155-167.
  6. Kitoogo Fredrick Edward, Venansius Baryamureeba & Guy De Pauw, "Towards Domain Independent Named Entity Recognition" In International Journal Of Computing And Ict Research, Vol. 2, No. 2, December 2008 Pp. 84-95
  7. L. F. Rau. "Extracting company names from text" In 7th IEEE Conference on Artifcial Intelligence Applications, volume i, pages 29{32, 1991.
  8. Satoshi Sekine. NYU: "Description of the Japanese NE system used for MET-2", In7th Message Understanding Conference (MUC-7, 1998.
  9. Satoshi Sekine and Chikashi Nobata. "Definition, Dictionaries and Tagger for Extended Named Entity Hierarchy", In 4th International Conference on Language Resources and Evaluation (LREC'04), Lisbon, Portugal, 2004
  10. J. Sim and C. C. Wright. "The Kappa Statistic in Reliability Studies: Use, Interpretation, and Sample Size Requirements. Physical Therapy", 85(3):257{268, January 2005.
  11. Giuseppe Rizzo and Raphael Troncy, "NERD: Evaluating Named Entity Recognition Tools in the Web of Data"
  12. David Palmer and David Day. "A statistical pro_le of the Named Entity task" In 5th International Conference on Applied Natural Language Processing, pages 190{193, Washington, USA, 1997.
  13. Enrique Alfonseca and Suresh Manandhar. "An Unsupervised Method for General Named Entity Recognition And Automated Concept Discovery" In 1st International Conference on General WordNet, 2002.
  14. Masayuki Asahara and Yuji Matsumoto. "Japanese Named Entity extraction with redundant morphological analysis" In International Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology (NAACL'03), pages 8{15, Edmonton, Canada, 2003.
  15. Daniel Bikel, Scott Miller, Richard Schwartz, and Ralph Weischedel. Nymble: "a high-performance learning name finder" , In 5th International Conference on Applied Natural Language Processing, pages 194{201, Washington, USA, 1997.
  16. Andrew Borthwick, John Sterling, Eugene Agichtein, and Ralph Grishman. "NYU: Description of the MENE Named Entity System as Used in MUC-7", in 7th Message Understanding Conference (MUC-7), 1998.
  17. Andrew McCallumand, Wei Li. "Early results for named entity recognition with conditional random fields, feature induction and web-enhanced lexicons", In 7th International Conference on Natural Language Learning at HLT-NAACL (CONLL'03), pages 188-191, Edmonton, Canada, 2003.
Index Terms

Computer Science
Information Sciences

Keywords

Introduction Ontology Architecture of Keyword Extractor Algorithm: Keyword Extraction Architecture of DSNER Algorithm: DSNER.

Powered by PhDFocusTM