Artificial Intelligence and Data Mining for Mergers and Acquisitions

The goal of this book is to present a modeling framework for the Virtual Organization that is focused on process composition. This framework uses Predicate Calculus Knowledge Bases. Petri Net-based modeling is also discussed. In this context, a Data Mining model is proposed, using a fuzzy mathematical approach, aiming to discover knowledge.A Knowledge-Based framework has been proposed in order to present an all-inclusive knowledge store for static and dynamic properties. Toward this direction, a Knowledge Base is created, and inferences are arrived at. This book features an advisory tool for Mergers and Acquisitions of Organizations using the Fuzzy Data Mining Framework and highlights the novelty of a Knowledge-Based Service-Oriented Architecture approach and development of an Enterprise Architectural model using AI that serves a wide audience. Students of Strategic Management in business schools and postgraduate programs in technology institutes seeking application areas of AI and Data Mining, as well as business/technology professionals in organizations aiming to create value through Mergers and Acquisitions and elsewhere, will benefit from the reading of this book. Dedication 6 Contents 8 Preface 12 Acknowledgments 14 About the Author 16 1. Introduction 18 2. Scope of the Book 20 3. Review of Related Work 22 4. Fuzzy Datamining Framework for Creation of Virtual Organization 28 5. UML Based Modeling of Business Processes & Discourse on Enterprise Architecture (EA)/Service Oriented Architecture (SOA) 34 6. Knowledge Representation Using Predicate Calculus 144 7. Petri Net Modeling of Business Processes 164 8. Conclusion 178 References 196 Index 202 The book proposal presents a modeling framework for Virtual Enterprise focused on process composition by consolidating individual process models into consolidated process model. This framework uses Artificial Intelligence Knowledge Bases and also proposes a Data Mining model using a fuzzy mathematical approach.