International Journal of Man-Machine Studies
C4.5: programs for machine learning
C4.5: programs for machine learning
Statistical inference and data mining
Communications of the ACM
Maintaining knowledge about temporal intervals
Communications of the ACM
Data-Driven Discovery of Quantitative Rules in Relational Databases
IEEE Transactions on Knowledge and Data Engineering
ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
Fuzzy Cognitive Agents for Personalized Recommendation
WISE '02 Proceedings of the 3rd International Conference on Web Information Systems Engineering
Computer aided fuzzy medical diagnosis
Information Sciences: an International Journal - Special issue: Medical expert systems
Medical Informatics: Knowledge Management and Data Mining in Biomedicine (Operations Research/Computer Science Interfaces)
Fuzzy Cognitive Agents in Shared Virtual Worlds
CW '05 Proceedings of the 2005 International Conference on Cyberworlds
Artificial Intelligence in Medicine
The temporal logic of programs
SFCS '77 Proceedings of the 18th Annual Symposium on Foundations of Computer Science
Extracting Temporal Rules from Medical Data
ICCTD '09 Proceedings of the 2009 International Conference on Computer Technology and Development - Volume 01
Mining temporal medical data using adaptive fuzzy cognitive maps
HSI'09 Proceedings of the 2nd conference on Human System Interactions
IEEE Transactions on Fuzzy Systems
Modeling complex systems using fuzzy cognitive maps
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
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Representation of temporal knowledge and analysis of temporal data is becoming a good practice for effective classification and prediction. Various semantic levels on knowledge representation schemes have been measured for temporal data. The existing Fuzzy Cognitive Maps FCMs facilitate modeling dynamic systems for knowledge representation and reasoning under uncertainty. However, the FCMs are constructed manually and are constrained by the human experts' validation for assessing its reliability and they are lacking in considering temporal features necessary for reasoning in medical applications. This paper proposes a new temporal mining system known as Fuzzy Temporal Cognitive Map FTCM, which defines a complete discrete temporal extension and fuzzy inference mechanism of FCM. In FTCM, the temporal dependencies of concepts during a particular time interval are measured. This work aims to reduce the complexities of dynamic modeling of a complex causal system by proposing a four layer fuzzy neural network to construct FTCM from the temporal data. In this proposed model, a fuzzy temporal mutual subsethood operator is used to measure the activation spread in the FTCM for automatic quantification of causalities. This FTCM is designed for a set of temporal clinical records, which can be further used for inferencing and prediction in medical diagnosis by generating a set of fuzzy temporal rules using Allen's temporal relationships and fuzzy temporal rules.