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21 produkter
21 produkter
Häftad, Engelska, 2019
997 kr
Skickas inom 10-15 vardagar
Due to market forces and technological evolution, Big Data computing is developing at an increasing rate. A wide variety of novel approaches and tools have emerged to tackle the challenges of Big Data, creating both more opportunities and more challenges for students and professionals in the field of data computation and analysis. Presenting a mix of industry cases and theory, Big Data Computing discusses the technical and practical issues related to Big Data in intelligent information management. Emphasizing the adoption and diffusion of Big Data tools and technologies in industry, the book introduces a broad range of Big Data concepts, tools, and techniques. It covers a wide range of research, and provides comparisons between state-of-the-art approaches. Comprised of five sections, the book focuses on: What Big Data is and why it is importantSemantic technologiesTools and methodsBusiness and economic perspectivesBig Data applications across industries
Häftad, Engelska, 2019
997 kr
Skickas inom 10-15 vardagar
The Internet has become an integral part of human life, yet the web still utilizes mundane interfaces to the physical world, which makes Internet operations somewhat mechanical, tedious, and less human-oriented. Filling a large void in the literature, Intelligent Technologies for Web Applications is one of the first books to focus on providing vital fundamental and advanced guidance in the area of Web intelligence for beginners and researchers.The book covers techniques from diverse areas of research, including:Natural language processingInformation extraction, retrieval, and filteringKnowledge representation and managementMachine learningDatabasesData, web, and text miningHuman–computer interactionSemantic web technologies To develop effective and intelligent web applications and services, it is critical to discover useful knowledge through analyzing large amounts of content, hidden content structures, or usage patterns of web data resources. Intended to improve and reinforce problem-solving methods in this area, this book delves into the hybridization of artificial intelligence (AI) and web technologies to help simplify complex Web operations. It introduces readers to the state-of-the art development of web intelligence techniques and teaches how to apply these techniques to develop the next generation of intelligent Web applications.The book lays out presented projects, case studies, and innovative ideas, which readers can explore independently as standalone research projects. This material facilitates experimentation with the book’s content by including fundamental tools, research directions, practice questions, and additional reading.
Häftad, Engelska, 2009
1 884 kr
Skickas inom 3-6 vardagar
A knowledge-based system (KBS) is a system that uses artificial intelligence techniques in problem-solving processes to support human decision-making, learning, and action. Ideal for advanced-undergraduate and graduate students, as well as business professionals, this text is designed to help users develop an appreciation of KBS and their architecture and understand a broad variety of knowledge-based techniques for decision support and planning. It assumes basic computer science skills and a math background that includes set theory, relations, elementary probability, and introductory concepts of artificial intelligence. Each of the 2 chapters is designed to be modular, providing instructors with the flexibility to model the book to their own course needs. Exercises are incorporated throughout the text to highlight certain aspects of the material presented and to simulate thought and discussion. A comprehensive text and resource, Knowledge-Based Systems provides access to the most current information in KBS and new artificial intelligences, as well as neural networks, fuzzy logic, genetic algorithms, and soft systems.
E-bok
Engelska, 20161 195 kr
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This reference presents both fundamental and advanced topics and related to Web operations. Using an integrated approach, the authors describe the basics as well as latest trends in the area. They cover agent-based Web, wrapper induction, Web mining, information retrieval, Web knowledge management, and social networks. The text includes a host of examples and over 100 illustrations that clarify complex material. It also contains many bibliographical notes, end-of-chapter exercises, glossaries, and practice questions with solutions/hints.
E-bok
Engelska, 2013970 kr
Läs direkt efter köp
Due to market forces and technological evolution, Big Data computing is developing at an increasing rate. A wide variety of novel approaches and tools have emerged to tackle the challenges of Big Data, creating both more opportunities and more challenges for students and professionals in the field of data computation and analysis. Novel approaches and tools have emerged to tackle the challenges of Big Data. Moreover, the technology required for Big Data computing is developing at a satisfactory rate due to market forces and technological evolution. This book presents a mix of theory and industry cases that discuss the technical and practical issues related to Big Data in intelligent information management. It emphasizes the adoption and diffusion of Big Data tools and technologies in real practical applications.
Inbunden, Engelska, 2012
2 476 kr
Skickas inom 10-15 vardagar
The Internet has become an integral part of human life, yet the web still utilizes mundane interfaces to the physical world, which makes Internet operations somewhat mechanical, tedious, and less human-oriented. Filling a large void in the literature, Intelligent Technologies for Web Applications is one of the first books to focus on providing vital fundamental and advanced guidance in the area of Web intelligence for beginners and researchers.The book covers techniques from diverse areas of research, including:Natural language processingInformation extraction, retrieval, and filteringKnowledge representation and managementMachine learningDatabasesData, web, and text miningHuman–computer interactionSemantic web technologies To develop effective and intelligent web applications and services, it is critical to discover useful knowledge through analyzing large amounts of content, hidden content structures, or usage patterns of web data resources. Intended to improve and reinforce problem-solving methods in this area, this book delves into the hybridization of artificial intelligence (AI) and web technologies to help simplify complex Web operations. It introduces readers to the state-of-the art development of web intelligence techniques and teaches how to apply these techniques to develop the next generation of intelligent Web applications.The book lays out presented projects, case studies, and innovative ideas, which readers can explore independently as standalone research projects. This material facilitates experimentation with the book’s content by including fundamental tools, research directions, practice questions, and additional reading.
Inbunden, Engelska, 2013
2 476 kr
Skickas inom 10-15 vardagar
Due to market forces and technological evolution, Big Data computing is developing at an increasing rate. A wide variety of novel approaches and tools have emerged to tackle the challenges of Big Data, creating both more opportunities and more challenges for students and professionals in the field of data computation and analysis. Presenting a mix of industry cases and theory, Big Data Computing discusses the technical and practical issues related to Big Data in intelligent information management. Emphasizing the adoption and diffusion of Big Data tools and technologies in industry, the book introduces a broad range of Big Data concepts, tools, and techniques. It covers a wide range of research, and provides comparisons between state-of-the-art approaches. Comprised of five sections, the book focuses on: What Big Data is and why it is importantSemantic technologiesTools and methodsBusiness and economic perspectivesBig Data applications across industries
E-bok
PDF, Engelska, 2013967 kr
Läs direkt efter köp
Due to market forces and technological evolution, Big Data computing is developing at an increasing rate. A wide variety of novel approaches and tools have emerged to tackle the challenges of Big Data, creating both more opportunities and more challenges for students and professionals in the field of data computation and analysis. Novel approaches and tools have emerged to tackle the challenges of Big Data. Moreover, the technology required for Big Data computing is developing at a satisfactory rate due to market forces and technological evolution. This book presents a mix of theory and industry cases that discuss the technical and practical issues related to Big Data in intelligent information management. It emphasizes the adoption and diffusion of Big Data tools and technologies in real practical applications.
Inbunden, Engelska, 2020
1 825 kr
Skickas inom 10-15 vardagar
This contributed volume discusses essential topics and the fundamentals for Big Data Emergency Management and primarily focusses on the application of Big Data for Emergency Management. It walks the reader through the state of the art, in different facets of the big disaster data field. This includes many elements that are important for these technologies to have real-world impact. This book brings together different computational techniques from: machine learning, communication network analysis, natural language processing, knowledge graphs, data mining, and information visualization, aiming at methods that are typically used for processing big emergency data. This book also provides authoritative insights and highlights valuable lessons by distinguished authors, who are leaders in this field.Emergencies are severe, large-scale, non-routine events that disrupt the normal functioning of a community or a society, causing widespread and overwhelming losses and impacts. Emergency Management is the process of planning and taking actions to minimize the social and physical impact of emergencies and reduces the community’s vulnerability to the consequences of emergencies. Information exchange before, during and after the disaster periods can greatly reduce the losses caused by the emergency. This allows people to make better use of the available resources, such as relief materials and medical supplies. It also provides a channel through which reports on casualties and losses in each affected area, can be delivered expeditiously. Big Data-Driven Emergency Management refers to applying advanced data collection and analysis technologies to achieve more effective and responsive decision-making during emergencies.Researchers, engineers and computer scientists working in Big Data Emergency Management, who need to deal with large and complex sets of data will want to purchase this book. Advanced-level students interested in data-driven emergency/crisis/disaster management will also want to purchase this book as a study guide.
E-bok
Engelska, 20202 359 kr
Läs direkt efter köp
This contributed volume discusses essential topics and the fundamentals for Big Data Emergency Management and primarily focusses on the application of Big Data for Emergency Management. It walks the reader through the state of the art, in different facets of the big disaster data field. This includes many elements that are important for these technologies to have real-world impact. This book brings together different computational techniques from: machine learning, communication network analysis, natural language processing, knowledge graphs, data mining, and information visualization, aiming at methods that are typically used for processing big emergency data. This book also provides authoritative insights and highlights valuable lessons by distinguished authors, who are leaders in this field.Emergencies are severe, large-scale, non-routine events that disrupt the normal functioning of a community or a society, causing widespread and overwhelming losses and impacts. Emergency Management is the process of planning and taking actions to minimize the social and physical impact of emergencies and reduces the community’s vulnerability to the consequences of emergencies. Information exchange before, during and after the disaster periods can greatly reduce the losses caused by the emergency. This allows people to make better use of the available resources, such as relief materials and medical supplies. It also provides a channel through which reports on casualties and losses in each affected area, can be delivered expeditiously. Big Data-Driven Emergency Management refers to applying advanced data collection and analysis technologies to achieve more effective and responsive decision-making during emergencies.Researchers, engineers and computer scientists working in Big Data Emergency Management, who need to deal with large and complex sets of data will want to purchase this book. Advanced-level students interested in data-driven emergency/crisis/disaster management will also want to purchase this book as a study guide.
Häftad, Engelska, 2021
1 825 kr
Skickas inom 10-15 vardagar
This contributed volume discusses essential topics and the fundamentals for Big Data Emergency Management and primarily focusses on the application of Big Data for Emergency Management. It walks the reader through the state of the art, in different facets of the big disaster data field. This includes many elements that are important for these technologies to have real-world impact. This book brings together different computational techniques from: machine learning, communication network analysis, natural language processing, knowledge graphs, data mining, and information visualization, aiming at methods that are typically used for processing big emergency data. This book also provides authoritative insights and highlights valuable lessons by distinguished authors, who are leaders in this field.Emergencies are severe, large-scale, non-routine events that disrupt the normal functioning of a community or a society, causing widespread and overwhelming losses and impacts. Emergency Management is the process of planning and taking actions to minimize the social and physical impact of emergencies and reduces the community’s vulnerability to the consequences of emergencies. Information exchange before, during and after the disaster periods can greatly reduce the losses caused by the emergency. This allows people to make better use of the available resources, such as relief materials and medical supplies. It also provides a channel through which reports on casualties and losses in each affected area, can be delivered expeditiously. Big Data-Driven Emergency Management refers to applying advanced data collection and analysis technologies to achieve more effective and responsive decision-making during emergencies.Researchers, engineers and computer scientists working in Big Data Emergency Management, who need to deal with large and complex sets of data will want to purchase this book. Advanced-level students interested in data-driven emergency/crisis/disaster management will also want to purchase this book as a study guide.
Del 1810 - Communications in Computer and Information Science
AI, Data, and Digitalization
First International Symposium, SAIDD 2023, Sogndal, Norway, May 9–10, 2023, Revised Selected Papers
Häftad, Engelska, 2024
448 kr
Skickas inom 10-15 vardagar
This open access book constitutes the revised selected papers of the First International Symposium on AI, Data and Digitalization, SAIDD 2023, held in Sogndal, Norway, during May 9–10, 2023.The 13 full papers included in this volume were carefully reviewed and selected from 42 submissions. The papers deal with the impact of data and AI on the digital revolution and their contribution to solving societal challenges.
Inbunden, Engelska, 2026
778 kr
Skickas inom 10-15 vardagar
Artificial Intelligence: Transcending Traditional Paradigms is a significant new introductory text for undergraduate and graduate course use. It introduces students and professionals to the state-of-the-art development of Artificial Intelligence techniques to develop smart real-world solutions. As an active researcher, the author presents the material authoritatively and with insights that reflect a modern, firsthand understanding of the field.Artificial intelligence is a science still in its infancy, and that makes it special. It’s not like more established fields, and the author has tried in writing this textbook to honour this characteristic and the ways it makes AI unique.
E-bok
Engelska, 2026978 kr
Läs direkt efter köp
Artificial Intelligence: Transcending Traditional Paradigms is a significant new introductory text for undergraduate and graduate course use. It introduces students and professionals to the state-of-the-art development of Artificial Intelligence techniques to develop smart real-world solutions. As an active researcher, the author presents the material authoritatively and with insights that reflect a modern, firsthand understanding of the field.Artificial intelligence is a science still in its infancy, and that makes it special. It’s not like more established fields, and the author has tried in writing this textbook to honour this characteristic and the ways it makes AI unique.
Inbunden, Engelska, 2016
833 kr
Skickas inom 10-15 vardagar
This textbook provides readers with the tools, techniques and cases required to excel with modern artificial intelligence methods. These embrace the family of neural networks, fuzzy systems and evolutionary computing in addition to other fields within machine learning, and will help in identifying, visualizing, classifying and analyzing data to support business decisions./p> The authors, discuss advantages and drawbacks of different approaches, and present a sound foundation for the reader to design and implement data analytic solutions for real‐world applications in an intelligent manner. Intelligent Techniques for Data Science also provides real-world cases of extracting value from data in various domains such as retail, health, aviation, telecommunication and tourism.
E-bok
PDF, Engelska, 20161 059 kr
Läs direkt efter köp
This textbook provides readers with the tools, techniques and cases required to excel with modern artificial intelligence methods. These embrace the family of neural networks, fuzzy systems and evolutionary computing in addition to other fields within machine learning, and will help in identifying, visualizing, classifying and analyzing data to support business decisions./p>
The authors, discuss advantages and drawbacks of different approaches, and present a sound foundation for the reader to design and implement data analytic solutions for real‐world applications in an intelligent manner. Intelligent Techniques for Data Science also provides real-world cases of extracting value from data in various domains such as retail, health, aviation, telecommunication and tourism.
Häftad, Engelska, 2018
833 kr
Skickas inom 10-15 vardagar
This textbook provides readers with the tools, techniques and cases required to excel with modern artificial intelligence methods. These embrace the family of neural networks, fuzzy systems and evolutionary computing in addition to other fields within machine learning, and will help in identifying, visualizing, classifying and analyzing data to support business decisions./p> The authors, discuss advantages and drawbacks of different approaches, and present a sound foundation for the reader to design and implement data analytic solutions for real‐world applications in an intelligent manner. Intelligent Techniques for Data Science also provides real-world cases of extracting value from data in various domains such as retail, health, aviation, telecommunication and tourism.
Häftad, Engelska, 2018
723 kr
Skickas inom 10-15 vardagar
The big data tsunami changes the perspective of industrial and academic research in how they address both foundational questions and practical applications. This calls for a paradigm shift in algorithms and the underlying mathematical techniques. There is a need to understand foundational strengths and address the state of the art challenges in big data that could lead to practical impact. The main goal of this book is to introduce algorithmic techniques for dealing with big data sets. Traditional algorithms work successfully when the input data fits well within memory. In many recent application situations, however, the size of the input data is too large to fit within memory.Models of Computation for Big Data, covers mathematical models for developing such algorithms, which has its roots in the study of big data that occur often in various applications. Most techniques discussed come from research in the last decade. The book will be structured as a sequence of algorithmic ideas, theoretical underpinning, and practical use of that algorithmic idea. Intended for both graduate students and advanced undergraduate students, there are no formal prerequisites, but the reader should be familiar with the fundamentals of algorithm design and analysis, discrete mathematics, probability and have general mathematical maturity.
E-bok
Engelska, 2018868 kr
Läs direkt efter köp
The big data tsunami changes the perspective of industrial and academic research in how they address both foundational questions and practical applications. This calls for a paradigm shift in algorithms and the underlying mathematical techniques. There is a need to understand foundational strengths and address the state of the art challenges in big data that could lead to practical impact. The main goal of this book is to introduce algorithmic techniques for dealing with big data sets. Traditional algorithms work successfully when the input data fits well within memory. In many recent application situations, however, the size of the input data is too large to fit within memory.
Models of Computation for Big Data, covers mathematical models for developing such algorithms, which has its roots in the study of big data that occur often in various applications. Most techniques discussed come from research in the last decade. The book will be structured as a sequence of algorithmic ideas, theoretical underpinning, and practical use of that algorithmic idea. Intended for both graduate students and advanced undergraduate students, there are no formal prerequisites, but the reader should be familiar with the fundamentals of algorithm design and analysis, discrete mathematics, probability and have general mathematical maturity.
Häftad, Engelska, 2018
888 kr
Skickas inom 10-15 vardagar
This book offers a practical guide to artificial intelligence (AI) techniques that are used in business. The book does not focus on AI models and algorithms, but instead provides an overview of the most popular and frequently used models in business. This allows the book to easily explain AI paradigms and concepts for business students and executives. Artificial Intelligence for Business is divided into six chapters. Chapter 1 begins with a brief introduction to AI and describes its relationship with machine learning, data science and big data analytics. Chapter 2 presents core machine learning workflow and the most effective machine learning techniques. Chapter 3 deals with deep learning, a popular technique for developing AI applications. Chapter 4 introduces recommendation engines for business and covers how to use them to be more competitive. Chapter 5 features natural language processing (NLP) for sentiment analysis focused on emotions. With the help of sentiment analysis, businesses can understand their customers better to improve their experience, which will help the businesses change their market position. Chapter 6 states potential business prospects of AI and the benefits that companies can realize by implementing AI in their processes.
E-bok
Engelska, 20181 141 kr
Läs direkt efter köp
This book offers a practical guide to artificial intelligence (AI) techniques that are used in business. The book does not focus on AI models and algorithms, but instead provides an overview of the most popular and frequently used models in business. This allows the book to easily explain AI paradigms and concepts for business students and executives. Artificial Intelligence for Business is divided into six chapters. Chapter 1 begins with a brief introduction to AI and describes its relationship with machine learning, data science and big data analytics. Chapter 2 presents core machine learning workflow and the most effective machine learning techniques. Chapter 3 deals with deep learning, a popular technique for developing AI applications. Chapter 4 introduces recommendation engines for business and covers how to use them to be more competitive. Chapter 5 features natural language processing (NLP) for sentiment analysis focused on emotions. With the help of sentiment analysis, businesses can understand their customers better to improve their experience, which will help the businesses change their market position. Chapter 6 states potential business prospects of AI and the benefits that companies can realize by implementing AI in their processes.