The nature of statistical learning theory
The nature of statistical learning theory
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
A semi-structured document model for text mining
Journal of Computer Science and Technology
Text Categorization with Suport Vector Machines: Learning with Many Relevant Features
ECML '98 Proceedings of the 10th European Conference on Machine Learning
A Comparative Study on Feature Selection in Text Categorization
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
SVMTorch: support vector machines for large-scale regression problems
The Journal of Machine Learning Research
Survey of Text Mining
Frequent Subtree Mining - An Overview
Fundamenta Informaticae - Advances in Mining Graphs, Trees and Sequences
XML Document Classification Using Extended VSM
Focused Access to XML Documents
Learning element similarity matrix for semi-structured document analysis
Knowledge and Information Systems
Overview of the INEX 2009 XML mining track: clustering and classification of XML documents
INEX'09 Proceedings of the Focused retrieval and evaluation, and 8th international conference on Initiative for the evaluation of XML retrieval
PKU at INEX 2010 XML mining track
INEX'10 Proceedings of the 9th international conference on Initiative for the evaluation of XML retrieval: comparative evaluation of focused retrieval
X-Class: Associative Classification of XML Documents by Structure
ACM Transactions on Information Systems (TOIS)
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Structured link vector model (SLVM) is a representation proposed for modeling XML documents, which was extended from the conventional vector space model (VSM) by incorporating document structures. In this paper, we describe the classification approach for XML documents based on SLVM in the Document Mining Challenge of INEX 2009, where the closed frequent subtrees as structural units are used for content extraction from the XML document and the Chi-square test is used for feature selection.