Generating association rules from semi-structured documents using an extended concept hierarchy
CIKM '97 Proceedings of the sixth international conference on Information and knowledge management
Query flocks: a generalization of association-rule mining
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Integrating association rule mining with relational database systems: alternatives and implications
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
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
Comparative analysis of five XML query languages
ACM SIGMOD Record
Why and how to benchmark XML databases
ACM SIGMOD Record
Discovering Structural Association of Semistructured Data
IEEE Transactions on Knowledge and Data Engineering
Set-Oriented Mining for Association Rules in Relational Databases
ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
A New SQL-like Operator for Mining Association Rules
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
Mining Association Rules from XML Data
DaWaK 2000 Proceedings of the 4th International Conference on Data Warehousing and Knowledge Discovery
Efficiently mining frequent trees in a forest
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
TreeFinder: a First Step towards XML Data Mining
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
A Tool for Extracting XML Association Rules
ICTAI '02 Proceedings of the 14th IEEE International Conference on Tools with Artificial Intelligence
Semantic networks as abstract data types
Semantic networks as abstract data types
Efficient Data Mining for Maximal Frequent Subtrees
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Discovering interesting information in XML data with association rules
Proceedings of the 2003 ACM symposium on Applied computing
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
Mining interesting XML-enabled association rules with templates
KDID'04 Proceedings of the Third international conference on Knowledge Discovery in Inductive Databases
Efficient online mining of large databases
International Journal of Business Information Systems
Tree model guided candidate generation for mining frequent subtrees from XML documents
ACM Transactions on Knowledge Discovery from Data (TKDD)
Object-relational complex structures for XML storage
Information and Software Technology
Modeling views for semantic web using extensible semantic (XSemantic) nets
OTM'05 Proceedings of the 2005 OTM Confederated international conference on On the Move to Meaningful Internet Systems
Mining changes from versions of dynamic XML documents
KDXD'06 Proceedings of the First international conference on Knowledge Discovery from XML Documents
Mining Induced/Embedded Subtrees using the Level of Embedding Constraint
Fundamenta Informaticae
Automated self-service modeling: predictive analytics as a service
Information Systems and e-Business Management
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Inspired by the good work of Han et al. (1996) and Elfeky et al. (2001) on the design of data mining query languages for relational and object-oriented databases, in this paper, we develop an expressive XML-enabled data mining query language by extension of XQuery. We first describe some preliminaries on the extension of traditional rule mining to XML mining. The philosophy that guides the language design is then elaborated. We detail the syntax of the mining language and its usage with a number of examples.