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The main goal of the field of data mining is the analysis of large and complex datasets. Some useful datasets may be derived from business and industrial activities. This kind of data is known as 'enterprise data'.

This book describes recently developed mathematical models, methodologies, and case studies in diverse areas, including stock market analysis, portfolio optimization, classification techniques in economics, supply chain optimization, development of e-commerce applications, etc.

Containing papers presented at the bilateral workshop by British and Lithuanian scientists, this book covers different topics on optimal design and operations, with emphasis on chemical engineering applications. It also considers a range of optimization methods, including deterministic, stochastic, global and hybrid methods.

Discusses the use of quantitative classification methods for the prediction of bank acquisitions. With an overview of the mergers and acquisitions (M&As) trends in the EU banking industry and a survey of the motives for M&As, this book compares various statistical and computational methodologies used to analyze and predict bank acquisitions.