Discovering typical structures of documents: a road map approach
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Clustering transactions using large items
Proceedings of the eighth international conference on Information and knowledge management
ACM Computing Surveys (CSUR)
XClust: clustering XML schemas for effective integration
Proceedings of the eleventh international conference on Information and knowledge management
PrefixSpan: Mining Sequential Patterns by Prefix-Projected Growth
Proceedings of the 17th International Conference on Data Engineering
Preparations for Semantics-Based XML Mining
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Optimized Substructure Discovery for Semi-structured Data
PKDD '02 Proceedings of the 6th European Conference on Principles of Data Mining and Knowledge Discovery
CLOPE: a fast and effective clustering algorithm for transactional data
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
WWW '03 Proceedings of the 12th international conference on World Wide Web
TreeFinder: a First Step towards XML Data Mining
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
Design and implement of customer information retrieval system based on semantic web
ICIC'06 Proceedings of the 2006 international conference on Intelligent computing: Part II
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We not only propose a method for XML document clustering using common structures but also show the application of our technique to XML retrieval. Our approach first extracts the frequent structures from XML documents by the decomposed method of tree. And then, we perform a new XML document clustering algorithm using common structures, which does not use measure of pairwise similarity between XML documents. The high speed and cluster cohesion of our clustering algorithm are shown in our experiment results.