
Applications of Data Mining in E-Business and Finance.
Title:
Applications of Data Mining in E-Business and Finance.
Author:
Soares, C.
ISBN:
9781607503545
Personal Author:
Physical Description:
1 online resource (156 pages)
Series:
Frontiers in Artificial Intelligence and Applications, v. 177 ; v.v. 177
Frontiers in Artificial Intelligence and Applications, v. 177
Contents:
Title page -- Preface -- Program Committee -- Contents -- Applications of Data Mining in E-Business and Finance: Introduction -- Evolutionary Optimization of Trading Strategies -- An Analysis of Support Vector Machines for Credit Risk Modeling -- Applications of Data Mining Methods in the Evaluation of Client Credibility -- A Tripartite Scorecard for the Pay/No Pay Decision-Making in the Retail Banking Industry -- An Apriori Based Approach to Improve On-Line Advertising Performance -- Probabilistic Latent Semantic Analysis for Search and Mining of Corporate Blogs -- A Quantitative Method for RSS Based Applications -- Comparing Negotiation Strategies Based on Offers -- Towards Business Interestingness in Actionable Knowledge Discovery -- A Deterministic Crowding Evolutionary Algorithm for Optimization of a KNN-Based Anomaly Intrusion Detection System -- Analysis of Foreign Direct Investment and Economic Development in the Yangtze Delta and Its Squeezing-in and out Effect -- Sequence Mining for Business Analytics: Building Project Taxonomies for Resource Demand Forecasting -- Author Index.
Abstract:
In spite of the close relationship between research and practice in Data Mining, it is not easy to find information on some of the important issues involved in real world application of DM technology. This book address some of these issues. It is suitable for Data Mining researchers and practitioners.
Local Note:
Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2017. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.
Genre:
Electronic Access:
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