Artificial Intelligence and Data Mining for Mergers and Acquisitions

This book provides a modeling framework for Virtual Organizations using Predicate Calculus Knowledge Bases and Petri Net-based modeling, along with a Data Mining model to discover knowledge. It also offers an advisory tool for Mergers and Acquisitions and highlights a Knowledge-Based Service-Oriented Architecture approach and Enterprise Architectural model using AI. Students and professionals in Strategic Management and technology institutes will benefit from this book.

\n Format: Hardback
\n Length: 188 pages
\n Publication date: 18 March 2021
\n Publisher: Taylor & Francis Ltd
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The aim of this book is to present a comprehensive modeling framework for Virtual Organizations, focusing on process composition. This framework utilizes Predicate Calculus Knowledge Bases, alongside Petri Net-based modeling. In this context, a Data Mining model is proposed, employing a fuzzy mathematical approach, with the goal of discovering knowledge.

A Knowledge-Based framework has been established to provide an all-encompassing knowledge store for static and dynamic properties. To achieve this, a Knowledge Base is created, and inferences are derived.

This book offers a valuable advisory tool for Mergers and Acquisitions of Organizations utilizing the Fuzzy Data Mining Framework. It also emphasizes the novelty of a Knowledge-Based Service-Oriented Architecture approach and the development of an Enterprise Architectural model using AI, catering to a broad 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 other endeavors, will greatly benefit from the insights and knowledge provided in this book.

\n Weight: 550g\n
Dimension: 184 x 261 x 19 (mm)\n
ISBN-13: 9781138354739\n \n