Discovering models of software processes from event-based data
ACM Transactions on Software Engineering and Methodology (TOSEM)
ACM SIGKDD Explorations Newsletter
Multi-dimensional sequential pattern mining
Proceedings of the tenth international conference on Information and knowledge management
Mining Sequential Patterns: Generalizations and Performance Improvements
EDBT '96 Proceedings of the 5th International Conference on Extending Database Technology: Advances in Database Technology
ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
Data Model Evolution as Basis of Business Process Management
OOER '95 Proceedings of the 14th International Conference on Object-Oriented and Entity-Relationship Modelling
Mining logs files for data-driven system management
ACM SIGKDD Explorations Newsletter - Natural language processing and text mining
A process of knowledge discovery from web log data: Systematization and critical review
Journal of Intelligent Information Systems
Automatic Business Process Pattern Matching for Enterprise Services Design
SERVICES-2 '09 Proceedings of the 2009 World Conference on Services - II
A Pattern-Based Framework of Change Operators for Ontology Evolution
OTM '09 Proceedings of the Confederated International Workshops and Posters on On the Move to Meaningful Internet Systems: ADI, CAMS, EI2N, ISDE, IWSSA, MONET, OnToContent, ODIS, ORM, OTM Academy, SWWS, SEMELS, Beyond SAWSDL, and COMBEK 2009
Mining process models with prime invisible tasks
Data & Knowledge Engineering
Change mining in adaptive process management systems
ODBASE'06/OTM'06 Proceedings of the 2006 Confederated international conference on On the Move to Meaningful Internet Systems: CoopIS, DOA, GADA, and ODBASE - Volume Part I
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Ontology change log data is a valuable source of information which reflects the changes in the domain, the user requirements, flaws in the initial design or the need to incorporate additional information. Ontology change logs can provide operational as well as analytical support in the ontology evolution process. In this paper, we present a novel approach to deal with change representation and knowledge discovery from ontology change logs. We look into different knowledge gathering aspects to capture every single facet of ontology change. The ontology changes are formalised using a graph-based approach. The knowledge-based change log facilitates detection of similarities within different time series, discovering implicit dependencies between ontological entities and reuse of knowledge. We analyse an ontology change log graph in order to identify frequent changes that occur in ontologies over time. We identify different types of change sequences based on their order and completeness. Analysis of change logs also assists in extracting new change patterns and rules which cannot be found by simply querying or processing ontology change logs.