C4.5: programs for machine learning
C4.5: programs for machine learning
An XML Log Standard and Tool for Digital Library Logging Analysis
ECDL '02 Proceedings of the 6th European Conference on Research and Advanced Technology for Digital Libraries
Mining and Reasoning on Workflows
IEEE Transactions on Knowledge and Data Engineering
Efficiently Mining Frequent Trees in a Forest: Algorithms and Applications
IEEE Transactions on Knowledge and Data Engineering
NDPMine: efficiently mining discriminative numerical features for pattern-based classification
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part II
Process Mining: Discovery, Conformance and Enhancement of Business Processes
Process Mining: Discovery, Conformance and Enhancement of Business Processes
Mining of Data with Complex Structures
Mining of Data with Complex Structures
XML documents clustering using a tensor space model
PAKDD'11 Proceedings of the 15th Pacific-Asia conference on Advances in knowledge discovery and data mining - Volume Part I
BPM'06 Proceedings of the 4th international conference on Business Process Management
A XML-Based workflow event logging mechanism for workflow mining
APWeb'06 Proceedings of the 2006 international conference on Advanced Web and Network Technologies, and Applications
A generic import framework for process event logs
BPM'06 Proceedings of the 2006 international conference on Business Process Management Workshops
XML document clustering using structure-preserving flat representation of XML content and structure
ADMA'11 Proceedings of the 7th international conference on Advanced Data Mining and Applications - Volume Part II
A structure preserving flat data format representation for tree-structured data
PAKDD'11 Proceedings of the 15th international conference on New Frontiers in Applied Data Mining
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Many data mining and simulation based algorithms have been applied in the process mining field; nevertheless they mainly focus on the process discovery and conformance checking tasks. Even though the event logs are increasingly represented in semi-structured format using XML-based templates, commonly used XML mining techniques have not been explored. In this paper, we investigate the application of tree mining techniques and propose a general framework, within which a wider range of structure aware data mining techniques can be applied. Decision tree learning and frequent pattern mining are used as a case in point in the experiments on publicly available real dataset. The results indicate the promising properties of the proposed framework in adding to the available set of tools for process log analysis by enabling (i) direct data mining of tree-structured process logs (ii) extraction of informative knowledge patterns and (iii) frequent pattern mining at lower minimum support thresholds.