Knowledge and Systems Engineering [electronic resource] : Proceedings of the Fifth International Conference KSE 2013, Volume 2 /
Huynh, Van Nam.editor.
Denoeux, Thierry.editor.
Tran, Dang Hung.editor.
Le, Anh Cuong.editor.
Pham, Son Bao.editor.
The field of Knowledge and Systems Engineering (KSE) has experienced rapid development and inspired many applications in the world of information technology during the last decade. The KSE conference aims at providing an open international forum for presentation, discussion and exchange of the latest advances and challenges in research of the field. These proceedings contain papers presented at the Fifth International Conference on Knowledge and Systems Engineering (KSE 2013), which was held in Hanoi, Vietnam, during 17–19 October, 2013. Besides the main track of contributed papers, which are compiled into the first volume, the conference also featured several special sessions focusing on specific topics of interest as well as included one workshop, of which the papers form the second volume of these proceedings. The book gathers a total of 68 papers describing recent advances and development on various topics including knowledge discovery and data mining, natural language processing, expert systems, intelligent decision making, computational biology, computational modeling, optimization algorithms, and industrial applications.
Description based upon print version of record.
""Preface""; ""Organization""; ""Contents""; ""Part I Workshop Invited Talks ""; ""The Place of Causal Analysis in the Analysis of Simulation Data""; ""Evolutionary Computation in the RealWorld: Successes and Challenges""; ""Part II KSE 2013 Special Sessions and Workshop ""; ""A Method of Two-Stage Clustering with Constraints Using Agglomerative Hierarchical Algorithm and One-Pass k-Means++ ""; ""1 Introduction""; ""2 Preliminary Consideration""; ""2.1 Agglomerative Hierarchical Clustering""; ""2.2 k-Means and k-Means++ ""; ""2.3 Pairwise Constraints""; ""3 A Two-Stage Algorithm""
""3.1 One-Pass COP k-Means++ """"3.2 Agglomerative Algorithm in the Second Stage""; ""4 Numerical Examples""; ""4.1 Evaluation by Objective Function Value""; ""4.2 Evaluation by RandIndex""; ""4.3 Evaluation by CPU Time""; ""5 Conclusion""; ""References""; ""An Algorithm Combining Spectral Clustering and DBSCAN for Core Points""; ""1 Introduction""; ""2 Preliminary Consideration""; ""2.1 Spectral Clustering""; ""2.2 DBSCAN-CORE""; ""3 Combining DBSCAN-CORE and Spectral Clustering""; ""3.1 Clusters of Data Set""; ""3.2 Other Related Algorithms""; ""4 Numerical Examples""
""4.1 Results for Artificial Data Sets""""4.2 The Iris Data Set""; ""5 Conclusion""; ""References""; ""Relational Fuzzy c-Means and Kernel Fuzzy c-Means Using a Quadratic Programming-Based Object-Wise Î² -Spread Transformation ""; ""1 Introduction""; ""2 Preliminaries""; ""2.1 RFCM and NERFCM""; ""2.2 K-FCM and IK-FCM""; ""3 Quadratic Programming-Based Object-Wise Î² -Spread Fuzzy Clustering ""; ""3.1 Concept of the Proposed Algorithms""; ""3.2 RFCM Using a Quadratic Programming-Based Object-Wise Î² -Spread Transformation ""
""3.3 K-FCM Using Quadratic Programming-Based Object-Wise Î² -Spread """"3.4 Relation between RFCM and K-FCM, NERFCM and IK-FCM, and qO-NERFCM and qO-IK-FCM""; ""4 Numerical Examples""; ""5 Conclusion""; ""References""; ""The Utilities of Imprecise Rules and Redundant Rules for Classifiers""; ""1 Introduction""; ""2 Rough Set Approach to Classification""; ""3 Imprecise Rules and Robustness""; ""3.1 Inducing Imprecise Rules and Classification""; ""3.2 Robustness""; ""4 Numerical Experiments""; ""4.1 Outline""; ""4.2 Data-Sets""; ""4.3 10-Fold Cross Validation""
""4.4 Performances of Imprecise Rules Induced by MLEM2""""4.5 The Performance of Classifier with Redundant Rules""; ""4.6 Effects of Imprecision in Rule Conclusions""; ""5 Concluding Remarks""; ""References""; ""On Cluster Extraction from Relational Data Using Entropy Based Relational Crisp Possibilistic Clustering""; ""1 Introduction""; ""2 Preparation""; ""2.1 Entropy Based Fuzzy c-Means Clustering ""; ""2.2 Entropy Based Relational Fuzzy c-Means Clustering ""; ""3 Entropy Based Relational Crisp Possibilistic Clustering""; ""3.1 Objective Function and Optimal Solution""
""3.2 Algorithm of Proposed Method""
Includes bibliographical references and index.
The field of Knowledge and Systems Engineering (KSE) has experienced rapid development and inspired many applications in the world of information technology during the last decade. The KSE conference aims at providing an open international forum for presentation, discussion and exchange of the latest advances and challenges in research of the field. These proceedings contain papers presented at the Fifth International Conference on Knowledge and Systems Engineering (KSE 2013), which was held in Hanoi, Vietnam, during 17–19 October, 2013. Besides the main track of contributed papers, which are compiled into the first volume, the conference also featured several special sessions focusing on specific topics of interest as well as included one workshop, of which the papers form the second volume of these proceedings. The book gathers a total of 68 papers describing recent advances and development on various topics including knowledge discovery and data mining, natural language processing, expert systems, intelligent decision making, computational biology, computational modeling, optimization algorithms, and industrial applications.
Computational intelligence.
Artificial intelligence.
Computational Intelligence.
Artificial Intelligence.

Advances in Intelligent Systems and Computing