Formation and Evolution Mechanism of Collaborative Communities: Theories and Methods

Author: Xu Jun
Publisher:
Publish Date: 2005-03-01
Features: The formation and evolution mechanisms of collaborative communities are new research topics in CSCW/CSCL. This book attempts to study collaborative problems from a computational perspective, introducing statistical learning theory, support vector machines, and kernel function methods (which are regarded as a fundamental framework for studying machine learning problems) into collaborative mechanism research. It investigates the formation and evolution mechanisms of collaborative communities based on similarity relationships from both theoretical and algorithmic aspects.
First, it analyzes the two-class classification problem for linearly separable data, deriving the primal and dual forms of the optimization problem for the optimal hard margin hyperplane (i.e., hard margin support vector machine). It further derives the optimization problems corresponding to the optimal soft margin hyperplane and the direct optimal hyperplane, discussing the algorithms for solving these optimization problems.
Next, it discusses the mathematical theoretical foundation of the optimality of the optimal hyperplane and studies the kernel function method for classification learning problems in linearly inseparable data.
Then, it introduces the key technologies for implementing CRA systems, simulation experiments, and discussions of the experimental results.
Finally, it points out several issues that require further research. This book is suitable for teachers and graduate students in computer science, automation, artificial intelligence, pattern recognition, and related fields at universities. It can also serve as a reference for scientists and engineers in related fields.