Machine Learning and Intelligent Decision Support Systems

Author: Yang Shanlin, Ni Zhiwei (editors)
Publisher:
Publish Date: 2004-08-01
Features: Research on machine learning is not only an important issue in artificial intelligence research but has also become one of the core issues in computer science and technology. Intelligent Decision Support Systems (IDSS) are a new type of information system formed by introducing artificial intelligence technology into Decision Support Systems (DSS). This book first studies the basic concepts of machine learning. On this basis, it details classic learning methods such as inductive learning, case-based reasoning, rough sets, and genetic algorithms. In the latter part of the book, it first introduces the relevant concepts of IDSS, then thoroughly explores IDSS based on several specific machine learning technologies. It not only studies the framework structure of machine learning-based IDSS but also investigates specific IDSS for various different machine learning techniques, including: neural network-based IDSS, case-based reasoning-based IDSS, genetic algorithm-based IDSS, inductive learning-based IDSS, and rough set-based IDSS. Additionally, it examines the integration of emerging machine learning technologies with IDSS. Finally, the book explores several related new technologies in IDSS. This book can serve as a textbook for undergraduate and graduate students in universities and colleges majoring in Information Management and Information Systems, E-commerce, Computer Science and Technology, and related fields. It can also be used as a reference book for computer application software developers and researchers. The book first introduces the basic concepts of IDSS and details classic learning methods such as inductive learning, case-based reasoning, rough sets, and genetic algorithms. In the latter part, it introduces relevant concepts and thoroughly explores IDSS based on several specific learning technologies. It not only studies the framework structure of machine learning-based IDSS but also investigates specific decision support systems for various different machine learning techniques. This book can serve as a teaching material for universities and colleges in Information Management and Information Systems, E-commerce, Computer Science and Technology, and can also be used as a reference for relevant researchers.