Knowledge discovery from structural data
Journal of Intelligent Information Systems
Clustering transactions using large items
Proceedings of the eighth international conference on Information and knowledge management
ACM Computing Surveys (CSUR)
Data mining: concepts and techniques
Data mining: concepts and techniques
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
Refining Initial Points for K-Means Clustering
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
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
BitCube: A Three-Dimensional Bitmap Indexing for XML Documents
SSDBM '01 Proceedings of the 13th International Conference on Scientific and Statistical Database Management
XML Clustering by Principal Component Analysis
ICTAI '04 Proceedings of the 16th IEEE International Conference on Tools with Artificial Intelligence
A tree-based approach to clustering XML documents by structure
PKDD '04 Proceedings of the 8th European Conference on Principles and Practice of Knowledge Discovery in Databases
Xproj: a framework for projected structural clustering of xml documents
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
XEdge: clustering homogeneous and heterogeneous XML documents using edge summaries
Proceedings of the 2008 ACM symposium on Applied computing
Clustering XML documents based on structural similarity
DASFAA'07 Proceedings of the 12th international conference on Database systems for advanced applications
A new sequential mining approach to XML document clustering*
APWeb'05 Proceedings of the 7th Asia-Pacific web conference on Web Technologies Research and Development
XCLS: a fast and effective clustering algorithm for heterogenous XML documents
PAKDD'06 Proceedings of the 10th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
Sequential pattern mining for structure-based XML document classification
INEX'05 Proceedings of the 4th international conference on Initiative for the Evaluation of XML Retrieval
Clustering XML documents using self-organizing maps for structures
INEX'05 Proceedings of the 4th international conference on Initiative for the Evaluation of XML Retrieval
XML clustering based on common neighbor
APWeb'06 Proceedings of the 2006 international conference on Advanced Web and Network Technologies, and Applications
Weigted-FP-tree based XML query pattern mining
ADMA'10 Proceedings of the 6th international conference on Advanced data mining and applications: Part I
FXProj: a fuzzy XML documents projected clustering based on structure and content
ADMA'11 Proceedings of the 7th international conference on Advanced Data Mining and Applications - Volume Part I
An efficient mining algorithm for maximal weighted frequent patterns in transactional databases
Knowledge-Based Systems
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XML has recently become very popular as a means of representing semistructured data and as a standard for data exchange over the Web, because of its varied applicability in numerous applications. Therefore, XML documents constitute an important data mining domain. In this paper, we propose a new method of XML document clustering by a global criterion function, considering the weight of common structures. Our approach initially extracts representative structures of frequent patterns from schemaless XML documents using a sequential pattern mining algorithm. Then, we perform clustering of an XML document by the weight of common structures, without a measure of pairwise similarity, assuming that an XML document is a transaction and frequent structures extracted from documents are items of the transaction. We conducted experiments to compare our method with previous methods. The experimental results show the effectiveness of our approach.