Author: Debasis Chanda
Publisher: CRC Press
ISBN: 0429755414
Category : Business & Economics
Languages : en
Pages : 205
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Book Description
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: Oliver Tensor
Publisher: Smart Creative Publishing
ISBN: 9781914067136
Category :
Languages : en
Pages : 122
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Book Description
Are you a new business owner? Or an entrepreneur looking to catch up to the big companies in your industrial sector? If you want to understand and master the fundamentals and importance of data science technologies to kick start your business or take it to the next level, then keep reading. Thanks to the smart and savvy customer of today, the competition to gain new customers while retaining the existing customers is fierce. As a result, companies are increasingly relying upon cutting edge technologies such as big data analytics, data mining technology, machine learning, and artificial intelligence technology to gain an edge over the competition.Today, machine learning and artificial intelligence have given rise to sophisticated machines that can study human behavior and activity to identify underlying human behavioral patterns and precisely predict what products and services consumers are interested in. Businesses with an eye on the future are gradually turning into technology companies under the façade of their intended business model. It is getting increasingly challenging for traditional businesses to retain their customers without adopting one or more of the cutting-edge technology explained in this book. Those entrepreneurs and business executives who have a sound understanding of the current challenges and status of their business will be primed to make informed decisions to meet the challenges head-on and improve their bottom line. Receive overarching guidance on how you can adopt any and all of the Data Science technologies in your business model to accelerate your growth rate. Learn how researchers are breaking the boundaries of data science to mimic human intelligence in machines. Learn the data science lifecycle in such extensive detail that you will be fully prepared to initiate and complete a data science implementation project in your business. Learn all about the historical development to the current explosion in this field of Big Data Analytics and how it differs data visualization techniques. Dig deep into the data mining process, the benefits of using data mining technology, the challenges facing the data mining technology and learn about some data mining tools that you can leverage for your business. Gain an in-depth understanding of various machine learning algorithms do assess the best Machine learning algorithm applicable to your business model. Learn the very important concept of data science and machine learning Decision Trees, applicable to small and large businesses across the industrial spectrum, explained thoroughly using real-life examples for ease of understanding. Master the concept of sales and marketing funnel along with the tools available for sales funnel analytics in the market today. Deep dive into the concept of personalized marketing, predictive analytics, customer analytics, and exploratory data analysis presented with details on how you can make sense out of all your customer behavioral data. This book is filled with real-life examples to help you understand the nitty-gritty of all the concepts as well as names and description of multiple tools that you can further explore and selectively implement in your business to reap the benefits of these cutting-edge technologies. Would You Like to Know More? Get This Book Today to get access to Artificial Intelligence and Machine Learning power.
Author: Boris Kovalerchuk
Publisher: Springer Science & Business Media
ISBN: 0306470187
Category : Computers
Languages : en
Pages : 323
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Book Description
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: AboulElla Hassanien
Publisher: Springer Nature
ISBN: 3031432479
Category : Technology & Engineering
Languages : en
Pages : 572
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Book Description
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: Vijay Govindarajan
Publisher: Harvard Business Press
ISBN: 1647826268
Category : Business & Economics
Languages : en
Pages : 138
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Book Description
Two world-renowned experts on innovation and digital strategy explore how real-time data and AI will radically transform physical products—and the companies that make them. Tech giants like Facebook, Amazon, and Google can collect real-time data from billions of users. For companies that design and manufacture physical products, that type of fluid, data-rich information used to be a pipe dream. Now, with the rise of cheap and powerful sensors, supercomputing, and artificial intelligence, things are changing—fast. In Fusion Strategy, world-renowned innovation guru Vijay Govindarajan and digital strategy expert Venkat Venkataraman offer a first-of-its-kind playbook that will help industrial companies combine what they do best—create physical products—with what digitals do best—use algorithms and AI to parse expansive, interconnected datasets—to make strategic connections that would otherwise be impossible. The laws of competitive advantage are changing, rewarding those who have the most robust, data-driven insights rather than the most valuable assets. To compete in the new digital age, companies need to use real-time data to turbocharge their products, strategies, and customer relationships. Those that don't risk falling on the wrong side of the next great digital divide. Fusion Strategy is the way forward.
Author: Glenn Fung
Publisher: Frontiers Media SA
ISBN: 2889718115
Category : Science
Languages : en
Pages : 135
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Book Description
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: Mohammad Shamsul Arefin
Publisher: Springer Nature
ISBN: 9811666369
Category : Technology & Engineering
Languages : en
Pages : 784
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Book Description
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.
Author: J. Mark Munoz
Publisher: Business Expert Press
ISBN: 1948198991
Category : Business & Economics
Languages : en
Pages : 134
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Book Description
Technological breakthroughs relating to artificial intelligence has redefined business operations worldwide. For example, the ways in which data is captured, processed, and utilized to optimize customer interactions has grown by leaps and bounds. The change is redefining the structural dynamics of business strategy, economic theory, and management concepts. Leading technology companies around the world have expanded their research in artificial intelligence. With IBM’s launch of Watson, a new cognitive era has started. Investment firms have backed numerous emerging artificial intelligence companies. Meanwhile, there is paucity of academic and business research on the subject. This book project is a pioneering examination of how artificial intelligence is transforming the contemporary business strategy.
Author: Mayank Kejriwal
Publisher: Springer Nature
ISBN: 3031190394
Category : Business & Economics
Languages : en
Pages : 165
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Book Description
This book provides a brief synthesis of the known implementations, opportunities and challenges at the intersection of artificial intelligence (AI) and modern industry beyond the big-four companies that traditionally consume and produce such advanced technology: Facebook, Amazon, Microsoft and Google. With this information, the author also makes some reasonable claims about the role of AI in future industries. The book draws on a broad range of material, including reports from consulting firms, published surveys, academic papers and books, and expert knowledge available to the author due to numerous collaborations in academia and industry on AI. It is rigorous rather than speculative, drawing on known findings and expert summaries, where available. This provides industry leaders and other interested stakeholders with an accessible review of contemporary perspectives on AI’s forward-looking role in industry as well as a clarifying guide on the major issues that companies are likely to face as they commence on this exciting path. Examines the likely role of AI in industries of the future, both known and unknown Presents use-cases of AI currently being explored across Big Tech, multi-national corporations and start-ups Explores the regulation of AI and its potential impacts on the workforce
Author: Yavuz Tansoy Yıldırım
Publisher: Turkuaz Kongre Organizasyonu Fuarcılık Yayıncılık Eğitim Turizm ve Ticaret Limited Şirketi
ISBN: 6256379888
Category : Business & Economics
Languages : en
Pages : 99
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Book Description
This book consists of six chapters. The book and its authors are: CHAPTER-1: PRICING STRATEGIES AND CUSTOMER BEHAVIOR IN THE TECHNOLOGY MARKETING PROCESS, Aydın HEYDAROV CHAPTER-2: INVESTMENT VALUATION ANALYSIS: THE ROLE OF ARTIFICIAL INTELLIGENCE TECHNIQUES, Elnura MAMMADOVA CHAPTER-3: ENHANCING COMPLIANCE WITH INTERNATIONAL PANDEMIC LAW IN THE CONTEXT OF INTERNATIONAL RELATIONS, Sabina Aliyeva & Elsevar Najafov CHAPTER-4: TOOLS TO INCREASE THE EFFICIENCY OF MANAGEMENT: THE EXAMPLE OF AGRICULTURAL ENTERPRISES, Sabina VALIYEVA CHAPTER-5: ERGONOMICS STRATEGY: AN EXAMPLE OF CREATING WORK-LIFE BALANCE, Nushaba MEHDIYEVA CHAPTER-6: EVOLUTIONARY EDUCATIONAL PSYCHOLOGY: HISTORY, PRACTICE, AND THE FUTURE, Ragib Muslum
