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
https://ieeexplore.ieee.org/xpl/conhome/4221263/proceeding
Source: DBLP
Preferred by: Hamid Bouchachia