alexa Classification of XML Document by Extracting Structura
ISSN ONLINE(2320-9801) PRINT (2320-9798)

International Journal of Innovative Research in Computer and Communication Engineering
Open Access

OMICS International organises 3000+ Global Conferenceseries Events every year across USA, Europe & Asia with support from 1000 more scientific Societies and Publishes 700+ Open Access Journals which contains over 50000 eminent personalities, reputed scientists as editorial board members.

Open Access Journals gaining more Readers and Citations

700 Journals and 15,000,000 Readers Each Journal is getting 25,000+ Readers

This Readership is 10 times more when compared to other Subscription Journals (Source: Google Analytics)

Special Issue Article

Classification of XML Document by Extracting Structural and Textual Features

Gnana Vardhini. H1,Anju Abraham2
  1. Student, Dept. of CSE, T. John Institute of Technology, Bengaluru, India
  2. Assistant Professor, Dept. of CSE, T. John Institute of Technology, Bengaluru, India
Related article at Pubmed, Scholar Google


In this paper the XML document classification is done by both structural and content based features. By this classification informative feature vectors are represented. In structural extraction, the tree-mining algorithm is used. For textual extraction, the algorithm is developed by using fuzzy c-means clustering algorithm. Once the classification is done the supervised classification algorithm is used which combines both structural and textual feature vectors. From which we get the classifier model. In this classification we can obtain 85% to 87% classification accuracy, which is more than the previously achieved classification accuracy.


Share This Page

Additional Info

Loading Please wait..
Peer Reviewed Journals
Make the best use of Scientific Research and information from our 700 + peer reviewed, Open Access Journals
International Conferences 2017-18
Meet Inspiring Speakers and Experts at our 3000+ Global Annual Meetings

Contact Us

© 2008-2017 OMICS International - Open Access Publisher. Best viewed in Mozilla Firefox | Google Chrome | Above IE 7.0 version