粗糙集与知识技术Rough sets and knowledge technology

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The scope of LNCS,including its subseries LNAI,spans the whole range of computer science and information technology including interdisciplinary topics in a variety of application fields.The type of material publised traditionally includes.
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Commemorative Paper
　Some Contributions by Zdzistaw Pawlak
Keynote Papers
　Conflicts and Negotations
　Hierarchical Machine Learning A Learning Methodology Inspired by Human Intelligence
　Rough-Fuzzy Granulation, Rough Entropy and Image Segmentation
　Towards Network Autonomy
Plenary Papers
　A Roadmap from Rough Set Theory to Granular Computing
　Partition Dependencies in Hierarchies of Probabilistic Decision Tables
　Knowledge Theory and Artificial Intelligence
　Applications of Knowledge Technologies to Sound and Vision Engineering
　A Rough Set Approach to Data with Missing Attribute Values
　Cognitive Neuroscience and Web Intelligence
　Cognitive Informatics and Contemporary Mathematics for Knowledge Manipulation
　Rough Mereological Reasoning in Rough Set Theory: Recent Results and Problems
　Theoretical Study of Granular Computing
　Knowledge Discovery by Relation Approximation: A Rough Set Approach
Rough Computing
　Reduction-Based Approaches Towards Constructing Galois (Concept) Lattices
　A New Discernibility Matrix and Function
　The Relationships Between Variable Precision Value and Knowledge Reduction Based on Variable Precision Rough Sets Model
　On Axiomatic Characterization of Approximation Operators Based on Atomic Boolean Algebras
　Rough Set Attribute Reduction in Decision Systems
　A New Extension Model of Rough Sets Under Incomplete Information
　Applying Rough Sets to Data Tables Containing Possibilistic Information
　Redundant Data Processing Based on Rough-Fuzzy
　……
Evolutionary Computing
Fuzzy Sets
Granular Computing
Neural Computing
Machine Learning and KDD
Logics and Reasoning
Multiagent Systems and Web Intelligence
Pattern Recognition
System Engineering and Description
Real-Life Applications Based on Knowledge Technology
Author Index