IDEAL 98 contains over 50 original contributions presenting some of the most recent development in data engineering: data processing, data analysis, and knowledge acquisition, with a particular focus on Financial Engineering and Data Mining. More specifically, these proceedings examine the following aspects of this emerging field, including: Under "Financial Engineering" - Stock and Portfolio Management; Genetic Algorithms for Computational Finance; Exchange Rate Prediction; Financial Applications. Under "Data Mining" - Probabilistic Learning; Clustering and Classification; Rule Extraction; Evolutionary Computing in Data Mining; Data Mining Applications. This volume is ideal for researchers, scientists, engineers, as well as other professionals who are interested in intelligent data engineering.
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1 of 1 people found the following review helpful:
5.0 out of 5 stars
Great book - interesting subject,
By Konstantinos Leonidou (Greece) - See all my reviews
This review is from: Intelligent Data Engineering and Learning (IDEAL 98): Perspectives on Financial Engineering and Data Mining (Paperback)
Very good approach to the subject. The book can be read from everyone either from people with mathematical and computer knowledge or people from finance and business domain. Excellent work!
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Inside This Book
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Key Phrases - Statistically Improbable Phrases (SIPs):
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annealed genetic algorithm, vector quantization engine, parameterised decision rule, frequent traversal sequences, hierarchical knowledge integration, pitch variation patterns, information handling agent, frequent traversal patterns, input variable reduction, trading rule parameter, financial data mining, class probability space, statistical arbitrage models, convex divergence, selected training patterns, odor attribute, current itemset, information agent manager, knowledge description language, synthetic asset, interval consequent, unsupervised learning system, color linking, perfect foresight model, fuzzy association rules Key Phrases - Capitalized Phrases (CAPs): (learn more)
Neural Networks, International Conference, Artificial Intelligence, New York, National Chengchi University, Technical Report, Department of Computer Science, Knowledge Discovery, Dynamic Neuro, Shangzheng Index, Morgan Kaufmann, Unified Statistical Learning Approach, Euro-Dollar Future, Sharpe Ratio, Large Databases, German Mark, Neural Computation, Menlo Park, World-Wide Web, Capital Markets, Securities Corporation, Product Date, Regents Park, Neural Information Processing Systems, Journal of Finance Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
annealed genetic algorithm, vector quantization engine, parameterised decision rule, frequent traversal sequences, hierarchical knowledge integration, pitch variation patterns, information handling agent, frequent traversal patterns, input variable reduction, trading rule parameter, financial data mining, class probability space, statistical arbitrage models, convex divergence, selected training patterns, odor attribute, current itemset, information agent manager, knowledge description language, synthetic asset, interval consequent, unsupervised learning system, color linking, perfect foresight model, fuzzy association rules Key Phrases - Capitalized Phrases (CAPs): (learn more)
Neural Networks, International Conference, Artificial Intelligence, New York, National Chengchi University, Technical Report, Department of Computer Science, Knowledge Discovery, Dynamic Neuro, Shangzheng Index, Morgan Kaufmann, Unified Statistical Learning Approach, Euro-Dollar Future, Sharpe Ratio, Large Databases, German Mark, Neural Computation, Menlo Park, World-Wide Web, Capital Markets, Securities Corporation, Product Date, Regents Park, Neural Information Processing Systems, Journal of Finance Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
Citations (learn more)
This book cites 56
books:
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- Data Mining by Jiawei Han on 7 pages
- Machine Learning by Tom M. Mitchell on page 282, page 322, and page 392
- Self-Organizing Maps by Teuvo Kohonen on page 41, page 288, and page 433
- Knowledge Discovery in Databases (Aaai Press Copublications) by Gregory Piatetsky-Shapiro on page 268, page 282, and page 418
- Advances in Knowledge Discovery and Data Mining (American Association for Artificial Intelligence) by Usama M. Fayyad on page 362, page 383, and page 417
See all 56 books this book cites
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