Integrating rules and connectionism for robust commonsense reasoning
Integrating rules and connectionism for robust commonsense reasoning
Fuzzy logic, neural networks, and soft computing
Communications of the ACM
Case-based reasoning
Soft computing in case based reasoning
Soft computing in case based reasoning
Bioinformatics: the machine learning approach
Bioinformatics: the machine learning approach
Soft Computing for Knowledge Discovery: Introducing Cartesian Granule Features
Soft Computing for Knowledge Discovery: Introducing Cartesian Granule Features
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
Rough-Fuzzy Hybridization: A New Trend in Decision Making
Rough-Fuzzy Hybridization: A New Trend in Decision Making
Neuro-Fuzzy Pattern Recognition: Methods in Soft Computing
Neuro-Fuzzy Pattern Recognition: Methods in Soft Computing
Case Generation Using Rough Sets with Fuzzy Representation
IEEE Transactions on Knowledge and Data Engineering
Foundations of Soft Case-Based Reasoning
Foundations of Soft Case-Based Reasoning
Interval Set Clustering of Web Users with Rough K-Means
Journal of Intelligent Information Systems
Classification and Learning Using Genetic Algorithms: Applications in Bioinformatics and Web Intelligence (Natural Computing Series)
Rough-Fuzzy C-Medoids Algorithm and Selection of Bio-Basis for Amino Acid Sequence Analysis
IEEE Transactions on Knowledge and Data Engineering
Rough–Fuzzy Collaborative Clustering
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Low-complexity fuzzy relational clustering algorithms for Web mining
IEEE Transactions on Fuzzy Systems
Data mining in soft computing framework: a survey
IEEE Transactions on Neural Networks
Web mining in soft computing framework: relevance, state of the art and future directions
IEEE Transactions on Neural Networks
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Data mining and knowledge discovery is described from pattern recognition point of view along with the relevance of soft computing. The concept of computational theory of perceptions (CTP), its characteristics and the relation with fuzzy-granulation (f-granulation) are explained. Role of f-granulation in machine and human intelligence, and its modeling through rough-fuzzy integration are discussed. Three examples of synergistic integration, e.g., roughfuzzy case generation, rough-fuzzy c-means and rough-fuzzy c-medoids are explained with their merits and role of fuzzy granular computation. Superiority, in terms of performance and computation time, is illustrated for the tasks of case generation (mining) in large scale case based reasoning systems, segmenting brain MR images, and analyzing protein sequences.