Rough set methods for the synthesis and analysis of concurrent processes
Rough set methods and applications
Data Streams: Models and Algorithms (Advances in Database Systems)
Data Streams: Models and Algorithms (Advances in Database Systems)
Knowledge Representation Techniques (Studies in Fuzziness and Soft Computing)
Knowledge Representation Techniques (Studies in Fuzziness and Soft Computing)
Monitoring, Security, and Rescue Techniques in Multiagent Systems (Advances in Soft Computing)
Monitoring, Security, and Rescue Techniques in Multiagent Systems (Advances in Soft Computing)
Learning Sunspot Classification
Fundamenta Informaticae - SPECIAL ISSUE ON CONCURRENCY SPECIFICATION AND PROGRAMMING (CS&P 2005) Ruciane-Nide, Poland, 28-30 September 2005
Genetic process mining: an experimental evaluation
Data Mining and Knowledge Discovery
Toward knowledge-rich data mining
Data Mining and Knowledge Discovery
Data Mining and Knowledge Discovery
Handbook of Granular Computing
Handbook of Granular Computing
Generalized theory of uncertainty (GTU)-principal concepts and ideas
Computational Statistics & Data Analysis
On-Line elimination of non-relevant parts of complex objects in behavioral pattern identification
PReMI'05 Proceedings of the First international conference on Pattern Recognition and Machine Intelligence
Eliciting domain knowledge in handwritten digit recognition
PReMI'05 Proceedings of the First international conference on Pattern Recognition and Machine Intelligence
Automatic planning of treatment of infants with respiratory failure through rough set modeling
RSCTC'06 Proceedings of the 5th international conference on Rough Sets and Current Trends in Computing
Behavioral pattern identification through rough set modelling
RSFDGrC'05 Proceedings of the 10th international conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing - Volume Part II
Discovering Concurrent Process Models in Data: A Rough Set Approach
RSFDGrC '09 Proceedings of the 12th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing
Synthesis of synchronized concurrent systems specified by information systems
RSKT'11 Proceedings of the 6th international conference on Rough sets and knowledge technology
A Rough Set Approach to Information Systems Decomposition
Fundamenta Informaticae - To Andrzej Skowron on His 70th Birthday
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The rapid expansion of the Internet has resulted not only in the ever growing amount of data therein stored, but also in the burgeoning complexity of the concepts and phenomena pertaining to those data. This issue has been vividly compared [14] by the renowned statistician, prof. Friedman of Stanford University, to the advances in human mobility from the period of walking afoot to the era of jet travel. These essential changes in data have brought new challenges to the development of new data mining methods, especially that the treatment of these data increasingly involves complex processes that elude classic modeling paradigms. "Hot" datasets like biomedical, financial or netuser behavior data are just a few examples. Mining such temporal or stream data is on the agenda of many research centers and companies worldwide (see, e.g., [31, 1]). In the data mining community, there is a rapidly growing interest in developing methods for the discovery of structures of temporal processes from data. Works on discovering models for processes from data have recently been undertaken by many renowned centers worldwide (e.g., [34, 19, 36, 9], www.isle.org/~langley/, soc.web.cse.unsw.edu.au/bibliography/discovery/index.html).