Classification of XML documents

Authors: Bouchachia, A. and Hassler, M.

Journal: Proceedings of the 2007 IEEE Symposium on Computational Intelligence and Data Mining, CIDM 2007

Pages: 390-396

ISBN: 9781424407057

DOI: 10.1109/CIDM.2007.368901

Abstract:

With the explosion of XML-based online documents, the task of knowledge discovery from the web becomes highly significant. As an appropriate machinery, classification allows to categorize documents to facilitate that task. A classification approach is introduced in this paper. It is based on the k-nearest neighborhood algorithm that relies on an edit distance measure. The originality of the work lies in combining both the content and the structure of XML documents to compute the edit distance. The approach is empirically evaluated using real-world XML collections. © 2007 IEEE.

Source: Scopus

Classification of XML documents

Authors: Bouchachia, A. and Hassler, M.

Journal: 2007 IEEE SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE AND DATA MINING, VOLS 1 AND 2

Pages: 390-396

ISBN: 978-1-4244-0705-7

DOI: 10.1109/CIDM.2007.368901

Source: Web of Science (Lite)

Classification of XML Documents.

Authors: Bouchachia, A. and Hassler, M.

Journal: CIDM

Pages: 390-396

Publisher: IEEE

http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=4221263

Source: DBLP

Preferred by: Hamid Bouchachia