A Novel Incremental Information Extraction Using Parse Tree Query Language And Parse Tree Databases
 | International Journal of Computer Trends and Technology (IJCTT) |  |
| © - October Issue 2013 by IJCTT Journal | ||
| Volume-4 Issue-10 | ||
| Year of Publication : 2013 | ||
| Authors :Rajula Srilatha , K. Murali |
Rajula Srilatha , K. Murali"A Novel Incremental Information Extraction Using Parse Tree Query Language And Parse Tree Databases "International Journal of Computer Trends and Technology (IJCTT),V4(10):3423-3429 October Issue 2013 .ISSN 2231-2803.www.ijcttjournal.org. Published by Seventh Sense Research Group.
Abstract:- Mining is nothing but retrieving the information from various resources .We have different approaches to retrieve these information one of them is traditional pipeline approach. As of increasing technologies it became more complicated to workout with these traditional approach the main drawback in these pipeline approach is if any modifications are done or any module is developed newly then we have to reapply the extraction .So we are developing the different approach for data mining in this paper is through database queries . These are optimized by databases that make this as efficient approach.
References -
[1] D. Ferrucci and A. Lally, “UIMA: An Architectural Approach to Unstructured Information ProcesSing in the Corporate Research Environment,” Natural Language Eng., vol. 10, nos. 3/4, pp. 327- 348, 2004.
[2] H. Cunningham, D. Maynard, K. Bontcheva, and V. Tablan, “GATE: A Framework and Graphical Development Environment for Robust NLP Tools and Applications,” Proc. 40th Ann. Meeting of the ACL, 2002.
[3] D. Grinberg, J. Lafferty, and D. Sleator, “A Robust ParSing Algorithm for Link Grammars,” Technical Report CMU-CS-TR- 95-125, Carnegie Mellon Univ. 1995.
[4] F. Chen, A. Doan, J. Yang, and R. Ramakrishnan, “Efficient Information Extraction over Evolving Text Data,” Proc IEEE 24th Int’l Conf. Data Eng. (ICDE ’08), pp. 943-952, 2008.
[5] F. Chen, B. Gao, A. Doan, J. Yang, and R. Ramakrishnan, “Optimizing Complex Extraction Programs over Evolving Text Data,” Proc 35th ACM SIGMOD Int’l Conf. Management of Data (SIGMOD ’09), pp. 321-334, 2009.
[6] S. Bird et al., “DeSigning and Evaluating an XPath Dialect for Linguistic Queries,” Proc 22nd Int’l Conf. Data Eng. (ICDE ’06), 2006.
[7] S. Sarawagi, “Information Extraction,” Foundations and Trends in Databases, vol. 1, no. 3, pp. 261-377, 2008.
[8] D.D. Sleator and D. Temperley, “ParSing English with a Link Grammar,” Proc Third Int’l Workshop ParSing Technologies, 1993.
[9] R. Leaman and G. Gonzalez, “BANNER: An Executable Survey of Advances in Biomedical Named Entity Recognition,” Proc. Pacific Symp. Biocomputing, pp. 652-663, 2008.
[10] A.R. Aronson, “Effective Mapping of Biomedical Text to the UMLS Metathesaurus: The MetaMap Program,” Proc. AMIA Symp., p. 17, 2001.
Keywords :— Text mining, query languages, information storage and retrieval