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Author : Debasis Chanda
Publisher :
ISBN 13 : 9780367720902
Total Pages : pages
Book Rating : 4.7/5 (29 download)
Download or read book Artificial Intelligence and Data Mining for Mergers and Acquisitions written by Debasis Chanda and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Debasis Chanda
Publisher : CRC Press
ISBN 13 : 0429755406
Total Pages : 263 pages
Book Rating : 4.4/5 (297 download)
Download or read book Artificial Intelligence and Data Mining for Mergers and Acquisitions written by Debasis Chanda and published by CRC Press. This book was released on 2021-03-18 with total page 263 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Author : Boris Kovalerchuk
Publisher : Springer Science & Business Media
ISBN 13 : 0306470187
Total Pages : 308 pages
Book Rating : 4.3/5 (64 download)
Download or read book Data Mining in Finance written by Boris Kovalerchuk and published by Springer Science & Business Media. This book was released on 2006-04-18 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Mining in Finance presents a comprehensive overview of major algorithmic approaches to predictive data mining, including statistical, neural networks, ruled-based, decision-tree, and fuzzy-logic methods, and then examines the suitability of these approaches to financial data mining. The book focuses specifically on relational data mining (RDM), which is a learning method able to learn more expressive rules than other symbolic approaches. RDM is thus better suited for financial mining, because it is able to make greater use of underlying domain knowledge. Relational data mining also has a better ability to explain the discovered rules - an ability critical for avoiding spurious patterns which inevitably arise when the number of variables examined is very large. The earlier algorithms for relational data mining, also known as inductive logic programming (ILP), suffer from a relative computational inefficiency and have rather limited tools for processing numerical data. Data Mining in Finance introduces a new approach, combining relational data mining with the analysis of statistical significance of discovered rules. This reduces the search space and speeds up the algorithms. The book also presents interactive and fuzzy-logic tools for `mining' the knowledge from the experts, further reducing the search space. Data Mining in Finance contains a number of practical examples of forecasting S&P 500, exchange rates, stock directions, and rating stocks for portfolio, allowing interested readers to start building their own models. This book is an excellent reference for researchers and professionals in the fields of artificial intelligence, machine learning, data mining, knowledge discovery, and applied mathematics.
Author : Kevin E. Voges
Publisher : IGI Global
ISBN 13 : 1591407028
Total Pages : 498 pages
Book Rating : 4.5/5 (914 download)
Download or read book Business Applications and Computational Intelligence written by Kevin E. Voges and published by IGI Global. This book was released on 2006-01-01 with total page 498 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book deals with the computational intelligence field, particularly business applications adopting computational intelligence techniques"--Provided by publisher.
Author : AboulElla Hassanien
Publisher : Springer Nature
ISBN 13 : 3031432479
Total Pages : 572 pages
Book Rating : 4.0/5 (314 download)
Download or read book Proceedings of the 9th International Conference on Advanced Intelligent Systems and Informatics 2023 written by AboulElla Hassanien and published by Springer Nature. This book was released on 2023-09-17 with total page 572 pages. Available in PDF, EPUB and Kindle. Book excerpt: This proceedings book constitutes the refereed proceedings of the 9th International Conference on Advanced Intelligent Systems and Informatics (AISI 2023), which took place in Port Said University, Port Said, Egypt, during September 20–22, 2023, Egypt, and is an international interdisciplinary conference that presents a spectrum of scientific research on all aspects of informatics and intelligent systems, technologies, and applications.
Author : Petra Perner
Publisher : Springer Science & Business Media
ISBN 13 : 3540441166
Total Pages : 115 pages
Book Rating : 4.5/5 (44 download)
Download or read book Advances in Data Mining written by Petra Perner and published by Springer Science & Business Media. This book was released on 2002-08-21 with total page 115 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents six thoroughly reviewed and revised full papers describing selected projects on data mining. Three papers deal with data mining and e-commerce, focusing on sequence rule analysis, association rule mining and knowledge discovery in databases, and intelligent e-marketing with Web mining. One paper is devoted to experience management and process learning. The last two papers report on medical applications, namely on genomic data processing and on case-based reasoning for prognosis of influenza.
Author : Bhavani Thuraisingham
Publisher : CRC Press
ISBN 13 : 1482252503
Total Pages : 288 pages
Book Rating : 4.4/5 (822 download)
Download or read book Data Mining written by Bhavani Thuraisingham and published by CRC Press. This book was released on 2014-01-23 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: Focusing on a data-centric perspective, this book provides a complete overview of data mining: its uses, methods, current technologies, commercial products, and future challenges. Three parts divide Data Mining: Part I describes technologies for data mining - database systems, warehousing, machine learning, visualization, decision support, statistics, parallel processing, and architectural support for data mining Part II presents tools and techniques - getting the data ready, carrying out the mining, pruning the results, evaluating outcomes, defining specific approaches, examining a specific technique based on logic programming, and citing literature and vendors for up-to-date information Part III examines emerging trends - mining distributed and heterogeneous data sources; multimedia data, such as text, images, video; mining data on the World Wide Web; metadata aspects of mining; and privacy issues. This self-contained book also contains two appendices providing exceptional information on technologies, such as data management, and artificial intelligence. Is there a need for mining? Do you have the right tools? Do you have the people to do the work? Do you have sufficient funds allocated to the project? All these answers must be answered before embarking on a project. Data Mining provides singular guidance on appropriate applications for specific techniques as well as thoroughly assesses valuable product information.
Author : Witold Abramowicz
Publisher : Springer Science & Business Media
ISBN 13 : 0792372433
Total Pages : 442 pages
Book Rating : 4.7/5 (923 download)
Download or read book Knowledge Discovery for Business Information Systems written by Witold Abramowicz and published by Springer Science & Business Media. This book was released on 2001 with total page 442 pages. Available in PDF, EPUB and Kindle. Book excerpt: Knowledge discovery (KDD) and Data Mining (DM) is a new, multidisciplinary field focusing on the process of information discovery from large volumes of data. The field combines such areas as database concepts and theory, machine learning, pattern recognition, and artificial intelligence.
Author : Evangelos Triantaphyllou
Publisher : Springer Science & Business Media
ISBN 13 : 0387342966
Total Pages : 784 pages
Book Rating : 4.3/5 (873 download)
Download or read book Data Mining and Knowledge Discovery Approaches Based on Rule Induction Techniques written by Evangelos Triantaphyllou and published by Springer Science & Business Media. This book was released on 2006-09-10 with total page 784 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book outlines the core theory and practice of data mining and knowledge discovery (DM & KD) examining theoretical foundations for various methods, and presenting an array of examples, many drawn from real-life applications. Most theoretical developments are accompanied by extensive empirical analysis, offering a deep insight into both theoretical and practical aspects of the subject. The book presents the combined research experiences of 40 expert contributors of world renown.
Author : Longbing Cao
Publisher : Springer Science & Business Media
ISBN 13 : 0387794204
Total Pages : 310 pages
Book Rating : 4.3/5 (877 download)
Download or read book Data Mining for Business Applications written by Longbing Cao and published by Springer Science & Business Media. This book was released on 2008-10-03 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Mining for Business Applications presents the state-of-the-art research and development outcomes on methodologies, techniques, approaches and successful applications in the area. The contributions mark a paradigm shift from “data-centered pattern mining” to “domain driven actionable knowledge discovery” for next-generation KDD research and applications. The contents identify how KDD techniques can better contribute to critical domain problems in theory and practice, and strengthen business intelligence in complex enterprise applications. The volume also explores challenges and directions for future research and development in the dialogue between academia and business.
Author : Mohammed J. Zaki
Publisher : Springer
ISBN 13 : 3540465022
Total Pages : 260 pages
Book Rating : 4.5/5 (44 download)
Download or read book Large-Scale Parallel Data Mining written by Mohammed J. Zaki and published by Springer. This book was released on 2003-07-31 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the unprecedented growth-rate at which data is being collected and stored electronically today in almost all fields of human endeavor, the efficient extraction of useful information from the data available is becoming an increasing scientific challenge and a massive economic need. This book presents thoroughly reviewed and revised full versions of papers presented at a workshop on the topic held during KDD'99 in San Diego, California, USA in August 1999 complemented by several invited chapters and a detailed introductory survey in order to provide complete coverage of the relevant issues. The contributions presented cover all major tasks in data mining including parallel and distributed mining frameworks, associations, sequences, clustering, and classification. All in all, the volume presents the state of the art in the young and dynamic field of parallel and distributed data mining methods. It will be a valuable source of reference for researchers and professionals.
Author : Jared Dean
Publisher : CreateSpace
ISBN 13 : 9781502462916
Total Pages : 318 pages
Book Rating : 4.4/5 (629 download)
Download or read book Big Data, Data Mining, and Machine Learning written by Jared Dean and published by CreateSpace. This book was released on 2014-09-23 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: With big data analytics comes big insights into profitability Big data is big business. But having the data and the computational power to process it isn't nearly enough to produce meaningful results. Big Data, Data Mining, and Machine Learning: Value Creation for Business Leaders and Practitioners is a complete resource for technology and marketing executives looking to cut through the hype and produce real results that hit the bottom line. Providing an engaging, thorough overview of the current state of big data analytics and the growing trend toward high performance computing architectures, the book is a detail-driven look into how big data analytics can be leveraged to foster positive change and drive efficiency. With continued exponential growth in data and ever more competitive markets, businesses must adapt quickly to gain every competitive advantage available. Big data analytics can serve as the linchpin for initiatives that drive business, but only if the underlying technology and analysis is fully understood and appreciated by engaged stakeholders. This book provides a view into the topic that executives, managers, and practitioners require, and includes: A complete overview of big data and its notable characteristics Details on high performance computing architectures for analytics, massively parallel processing (MPP), and in-memory databases Comprehensive coverage of data mining, text analytics, and machine learning algorithms A discussion of explanatory and predictive modeling, and how they can be applied to decision-making processes Big Data, Data Mining, and Machine Learning provides technology and marketing executives with the complete resource that has been notably absent from the veritable libraries of published books on the topic. Take control of your organization's big data analytics to produce real results with a resource that is comprehensive in scope and light on hyperbole.
Author : Longbing Cao
Publisher : Springer
ISBN 13 : 3642276091
Total Pages : 361 pages
Book Rating : 4.6/5 (422 download)
Download or read book Agents and Data Mining Interaction written by Longbing Cao and published by Springer. This book was released on 2011-12-18 with total page 361 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-workshop proceedings of the 7th International Workshop on Agents and Data Mining Interaction, ADMI 2011, held in Taipei, Taiwan, in May 2011 in conjunction with AAMAS 2011, the 10th International Joint Conference on Autonomous Agents and Multiagent Systems. The 11 revised full papers presented were carefully reviewed and selected from 24 submissions. The papers are organized in topical sections on agents for data mining; data mining for agents; and agent mining applications.
Author : Glenn Fung
Publisher : Frontiers Media SA
ISBN 13 : 2889718115
Total Pages : 135 pages
Book Rating : 4.8/5 (897 download)
Download or read book Artificial Intelligence in Insurance and Finance written by Glenn Fung and published by Frontiers Media SA. This book was released on 2022-01-04 with total page 135 pages. Available in PDF, EPUB and Kindle. Book excerpt: Luisa Fernanda Polania Cabrera is an Experienced Professional at Target Corporation (United States). Victor Wu is a Product Manager at GitLab Inc, San Francisco, United States. Sou-Cheng Choi is a Consulting Principle Data Scientist at Allstate Corporation. Lawrence Kwan Ho Ma is the Founder, Director and Chief Scientist of Valigo Limited and Founder, CEO and Chief Scientist of EMALI.IO Limited. Glenn M. Fung is the Chief Research Scientist at American Family Insurance.
Author : Jared Dean
Publisher : John Wiley & Sons
ISBN 13 : 1118618041
Total Pages : 293 pages
Book Rating : 4.1/5 (186 download)
Download or read book Big Data, Data Mining, and Machine Learning written by Jared Dean and published by John Wiley & Sons. This book was released on 2014-05-27 with total page 293 pages. Available in PDF, EPUB and Kindle. Book excerpt: With big data analytics comes big insights into profitability Big data is big business. But having the data and the computational power to process it isn't nearly enough to produce meaningful results. Big Data, Data Mining, and Machine Learning: Value Creation for Business Leaders and Practitioners is a complete resource for technology and marketing executives looking to cut through the hype and produce real results that hit the bottom line. Providing an engaging, thorough overview of the current state of big data analytics and the growing trend toward high performance computing architectures, the book is a detail-driven look into how big data analytics can be leveraged to foster positive change and drive efficiency. With continued exponential growth in data and ever more competitive markets, businesses must adapt quickly to gain every competitive advantage available. Big data analytics can serve as the linchpin for initiatives that drive business, but only if the underlying technology and analysis is fully understood and appreciated by engaged stakeholders. This book provides a view into the topic that executives, managers, and practitioners require, and includes: A complete overview of big data and its notable characteristics Details on high performance computing architectures for analytics, massively parallel processing (MPP), and in-memory databases Comprehensive coverage of data mining, text analytics, and machine learning algorithms A discussion of explanatory and predictive modeling, and how they can be applied to decision-making processes Big Data, Data Mining, and Machine Learning provides technology and marketing executives with the complete resource that has been notably absent from the veritable libraries of published books on the topic. Take control of your organization's big data analytics to produce real results with a resource that is comprehensive in scope and light on hyperbole.
Author : T. Warren Liao
Publisher : World Scientific
ISBN 13 : 9812779868
Total Pages : 816 pages
Book Rating : 4.8/5 (127 download)
Download or read book Recent Advances in Data Mining of Enterprise Data written by T. Warren Liao and published by World Scientific. This book was released on 2008-01-15 with total page 816 pages. Available in PDF, EPUB and Kindle. Book excerpt: The main goal of the new field of data mining is the analysis of large and complex datasets. Some very important datasets may be derived from business and industrial activities. This kind of data is known as OC enterprise dataOCO. The common characteristic of such datasets is that the analyst wishes to analyze them for the purpose of designing a more cost-effective strategy for optimizing some type of performance measure, such as reducing production time, improving quality, eliminating wastes, or maximizing profit. Data in this category may describe different scheduling scenarios in a manufacturing environment, quality control of some process, fault diagnosis in the operation of a machine or process, risk analysis when issuing credit to applicants, management of supply chains in a manufacturing system, or data for business related decision-making. Sample Chapter(s). Foreword (37 KB). Chapter 1: Enterprise Data Mining: A Review and Research Directions (655 KB). Contents: Enterprise Data Mining: A Review and Research Directions (T W Liao); Application and Comparison of Classification Techniques in Controlling Credit Risk (L Yu et al.); Predictive Classification with Imbalanced Enterprise Data (S Daskalaki et al.); Data Mining Applications of Process Platform Formation for High Variety Production (J Jiao & L Zhang); Multivariate Control Charts from a Data Mining Perspective (G C Porzio & G Ragozini); Maintenance Planning Using Enterprise Data Mining (L P Khoo et al.); Mining Images of Cell-Based Assays (P Perner); Support Vector Machines and Applications (T B Trafalis & O O Oladunni); A Survey of Manifold-Based Learning Methods (X Huo et al.); and other papers. Readership: Graduate students in engineering, computer science, and business schools; researchers and practioners of data mining with emphazis of enterprise data mining."
Author : Mohammad Shamsul Arefin
Publisher : Springer Nature
ISBN 13 : 9811666369
Total Pages : 784 pages
Book Rating : 4.8/5 (116 download)
Download or read book Proceedings of the International Conference on Big Data, IoT, and Machine Learning written by Mohammad Shamsul Arefin and published by Springer Nature. This book was released on 2021-12-03 with total page 784 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers a collection of high-quality peer-reviewed research papers presented at the International Conference on Big Data, IoT and Machine Learning (BIM 2021), held in Cox’s Bazar, Bangladesh, during 23–25 September 2021. The book covers research papers in the field of big data, IoT and machine learning. The book will be helpful for active researchers and practitioners in the field.
