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Reseach Article

Fast Computational Mining Technique for XML Query Answering Support

by R. Brindhadevi, J. Jabez
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 92 - Number 4
Year of Publication: 2014
Authors: R. Brindhadevi, J. Jabez
10.5120/15997-4915

R. Brindhadevi, J. Jabez . Fast Computational Mining Technique for XML Query Answering Support. International Journal of Computer Applications. 92, 4 ( April 2014), 18-24. DOI=10.5120/15997-4915

@article{ 10.5120/15997-4915,
author = { R. Brindhadevi, J. Jabez },
title = { Fast Computational Mining Technique for XML Query Answering Support },
journal = { International Journal of Computer Applications },
issue_date = { April 2014 },
volume = { 92 },
number = { 4 },
month = { April },
year = { 2014 },
issn = { 0975-8887 },
pages = { 18-24 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume92/number4/15997-4915/ },
doi = { 10.5120/15997-4915 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:14:32.622613+05:30
%A R. Brindhadevi
%A J. Jabez
%T Fast Computational Mining Technique for XML Query Answering Support
%J International Journal of Computer Applications
%@ 0975-8887
%V 92
%N 4
%P 18-24
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The database research field has focused on the Extensible Mark-up Language (XML) because of its adaptable progressive nature which can use to represent to huge amount of data, likewise it doesn't have absolute and fixed schema, yet having possibly spasmodic and deficient structure. Quite hard undertaking to concentrate data from semi organized documents and is set to wind up more challenging as the measure of computerized data accessible on the Internet develops. Really, the data set returned as response to a query may be so enormous it is not possible pass on interpretable information, as documents are regularly so extensive. A methodology based on Tree- Based Association Rules (TARs), which furnish rough, intentionaldata about the structure and the contents of XML documents both, and additionally it might be saved in XML format. This mined information is utilized to give, a brief thought of both the structure and the content of the XML archive and snappy, inexact replies to queries at whatever point needed.

References
  1. Agrawal. R and Srikant. R, "Fast Algorithms for Mining Association Rules in Large Databases," 2004, Proc. 20th Int'l Conf. Very Large Data Bases, pp. 478-499.
  2. Baralis. E, Garza. P, Quintarelli, and Tanca. L, "Answering XML Queries by Means of Data Summaries," vol . 25, 2007 ACM Trans. Information Systems, p. no. 3, p. 10.
  3. Barbosa. D, Mignet. L, and Veltri. P, "Studying the XML Web: Gathering Statistics from an XML Sample," World Wide Web, vol. 8, no. 4, 2005, pp. 413-438.
  4. Braga. D,. Campi. A, Ceri. S, Klemettinen. M, and Lanzi. P, "Discovering Interesting Information in XML Data with Association Rules," 2003,Proc. ACM Symp. Applied Computing, pp. 450-454.
  5. Chi. Y,Yang. Y, Xia. Y, and Muntz. R. R, "CMTreeMiner: Mining both Closed and Maximal Frequent Subtrees," 2004, Proc. Eighth Pacific- Asia Conf. Knowledge Discovery and Data Mining, pp. 63-73.
  6. Evfimievski. A, Srikant. R, Agrawal. R, and Gehrke. J, "PrivacyPreserving Mining of Association Rules,"2012, Proc. Eighth ACM Int'l Conf. Knowledge Discovery and Data Mining, pp. 217-228.
  7. Gasparini. S and Quintarelli. E, "Intensional Query Answering to XQuery Expressions," 2005, Proc. 16th Int'l Conf. Database and Expert Systems Applications, pp. 544-553.
  8. Mazuran. M, Quintarelli. E, and Tanca. L, "Mining Tree-Based Association Rules from XML Documents," technical report, 2009, Politecnicodi Milano, http://home. dei. polimi. it/quintare/Papers/MQT09-RR. pdf,
  9. Paik. J, Youn. H. Y and Kim. U. M, "A New Method for Mining Association Rules from a Collection of XML Documents,"2005, Proc. Int'l Conf. Computational Science and Its Applications, pp. 936-945.
  10. Termier. A, Rousset. M, and Sebag. M, "Dryade: A New Approach for Discovering Closed Frequent Trees in Heterogeneous Tree Databases,"2004, Proc. IEEE Fourth Int'l Conf. Data Mining, pp. 543-546
  11. World Wide Web Consortium, XML Schema, http://www. w3c. org/TR/xml schema,2001. www. w3C. org/xml-info set/, 2001.
  12. W3C XML Schema,2001. http://www. w3C. org/TR/xmlschema-1/.
  13. W3C. XML information Set, 2001. http://www. w3C. org/xml-infoset/.
  14. W3C. XQuery 1. 0: An xml query language, 2007. http://www. w3C. org/TR/xquery.
  15. Wang. K. and Liu. Discovering typical structures of documents: a roadmap approach. In Proc. of the 21st Int. Conf. on Research.
Index Terms

Computer Science
Information Sciences

Keywords

Extensible mark-up Language (XML) query answering data mining intentionaldata Tree-Based Association Rules.