A flexible model for retrieval of SGML documents
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Learning to extract symbolic knowledge from the World Wide Web
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
The Hierarchical Hidden Markov Model: Analysis and Applications
Machine Learning
Hierarchical classification of Web content
SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
A classifier for semi-structured documents
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Learning to construct knowledge bases from the World Wide Web
Artificial Intelligence - Special issue on Intelligent internet systems
Machine learning in automated text categorization
ACM Computing Surveys (CSUR)
A Study of Approaches to Hypertext Categorization
Journal of Intelligent Information Systems
Naive (Bayes) at Forty: The Independence Assumption in Information Retrieval
ECML '98 Proceedings of the 10th European Conference on Machine Learning
Text Categorization with Suport Vector Machines: Learning with Many Relevant Features
ECML '98 Proceedings of the 10th European Conference on Machine Learning
Classification of HTML Documents by Hidden Tree-Markov Models
ICDAR '01 Proceedings of the Sixth International Conference on Document Analysis and Recognition
A computational model for causal and diagnostic reasoning in inference systems
IJCAI'83 Proceedings of the Eighth international joint conference on Artificial intelligence - Volume 1
Structured multimedia document classification
Proceedings of the 2003 ACM symposium on Document engineering
An Evaluation of Passage-Based Text Categorization
Journal of Intelligent Information Systems
Bayesian networks and information retrieval: an introduction to the special issue
Information Processing and Management: an International Journal - Special issue: Bayesian networks and information retrieval
A bottom-up approach for XML documents classification
IDEAS '08 Proceedings of the 2008 international symposium on Database engineering & applications
Efficient rule based structural algorithms for classification of tree structured data
Intelligent Data Analysis
Possibilistic networks for information retrieval
International Journal of Approximate Reasoning
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We present a generative Bayesian model for the modeling of structured (e.g. XML) documents. This model allows us to simultaneously take into account structure and content information. It is used here for classifying XML documents. We adopt a machine learning approach and the model parameters are learned from a labeled training set of representative documents. We discuss the role of structural information for classification and describe experiments on a small collection of class labeled structured documents. We also present preliminary results showing how this model could classify documents with DTDs not represented in the training set.