Context-Aware Machine Learning and Mobile Data Analytics PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Context-Aware Machine Learning and Mobile Data Analytics PDF full book. Access full book title Context-Aware Machine Learning and Mobile Data Analytics by Iqbal Sarker. Download full books in PDF and EPUB format.
Author: Iqbal Sarker
Publisher: Springer Nature
ISBN: 3030885305
Category : Computers
Languages : en
Pages : 164
Get Book Here
Book Description
This book offers a clear understanding of the concept of context-aware machine learning including an automated rule-based framework within the broad area of data science and analytics, particularly, with the aim of data-driven intelligent decision making. Thus, we have bestowed a comprehensive study on this topic that explores multi-dimensional contexts in machine learning modeling, context discretization with time-series modeling, contextual rule discovery and predictive analytics, recent-pattern or rule-based behavior modeling, and their usefulness in various context-aware intelligent applications and services. The presented machine learning-based techniques can be employed in a wide range of real-world application areas ranging from personalized mobile services to security intelligence, highlighted in the book. As the interpretability of a rule-based system is high, the automation in discovering rules from contextual raw data can make this book more impactful for the application developers as well as researchers. Overall, this book provides a good reference for both academia and industry people in the broad area of data science, machine learning, AI-Driven computing, human-centered computing and personalization, behavioral analytics, IoT and mobile applications, and cybersecurity intelligence.
Author: Iqbal Sarker
Publisher: Springer Nature
ISBN: 3030885305
Category : Computers
Languages : en
Pages : 164
Get Book Here
Book Description
This book offers a clear understanding of the concept of context-aware machine learning including an automated rule-based framework within the broad area of data science and analytics, particularly, with the aim of data-driven intelligent decision making. Thus, we have bestowed a comprehensive study on this topic that explores multi-dimensional contexts in machine learning modeling, context discretization with time-series modeling, contextual rule discovery and predictive analytics, recent-pattern or rule-based behavior modeling, and their usefulness in various context-aware intelligent applications and services. The presented machine learning-based techniques can be employed in a wide range of real-world application areas ranging from personalized mobile services to security intelligence, highlighted in the book. As the interpretability of a rule-based system is high, the automation in discovering rules from contextual raw data can make this book more impactful for the application developers as well as researchers. Overall, this book provides a good reference for both academia and industry people in the broad area of data science, machine learning, AI-Driven computing, human-centered computing and personalization, behavioral analytics, IoT and mobile applications, and cybersecurity intelligence.
Author: Fa-Long Luo
Publisher: John Wiley & Sons
ISBN: 1119562252
Category : Technology & Engineering
Languages : en
Pages : 490
Get Book Here
Book Description
A comprehensive review to the theory, application and research of machine learning for future wireless communications In one single volume, Machine Learning for Future Wireless Communications provides a comprehensive and highly accessible treatment to the theory, applications and current research developments to the technology aspects related to machine learning for wireless communications and networks. The technology development of machine learning for wireless communications has grown explosively and is one of the biggest trends in related academic, research and industry communities. Deep neural networks-based machine learning technology is a promising tool to attack the big challenge in wireless communications and networks imposed by the increasing demands in terms of capacity, coverage, latency, efficiency flexibility, compatibility, quality of experience and silicon convergence. The author – a noted expert on the topic – covers a wide range of topics including system architecture and optimization, physical-layer and cross-layer processing, air interface and protocol design, beamforming and antenna configuration, network coding and slicing, cell acquisition and handover, scheduling and rate adaption, radio access control, smart proactive caching and adaptive resource allocations. Uniquely organized into three categories: Spectrum Intelligence, Transmission Intelligence and Network Intelligence, this important resource: Offers a comprehensive review of the theory, applications and current developments of machine learning for wireless communications and networks Covers a range of topics from architecture and optimization to adaptive resource allocations Reviews state-of-the-art machine learning based solutions for network coverage Includes an overview of the applications of machine learning algorithms in future wireless networks Explores flexible backhaul and front-haul, cross-layer optimization and coding, full-duplex radio, digital front-end (DFE) and radio-frequency (RF) processing Written for professional engineers, researchers, scientists, manufacturers, network operators, software developers and graduate students, Machine Learning for Future Wireless Communications presents in 21 chapters a comprehensive review of the topic authored by an expert in the field.
Author: Bader Alyoubi
Publisher: Springer Nature
ISBN: 3031184831
Category : Technology & Engineering
Languages : en
Pages : 214
Get Book Here
Book Description
This book presents advances in business computing and data analytics by discussing recent and innovative machine learning methods that have been designed to support decision-making processes. These methods form the theoretical foundations of intelligent management systems, which allows for companies to understand the market environment, to improve the analysis of customer needs, to propose creative personalization of contents, and to design more effective business strategies, products, and services. This book gives an overview of recent methods – such as blockchain, big data, artificial intelligence, and cloud computing – so readers can rapidly explore them and their applications to solve common business challenges. The book aims to empower readers to leverage and develop creative supervised and unsupervised methods to solve business decision-making problems.
Author: Md. Shahriare Satu
Publisher: Springer Nature
ISBN: 303134619X
Category : Computers
Languages : en
Pages : 597
Get Book Here
Book Description
The two-volume set LNICST 490 and 491 constitutes the proceedings of the First International Conference on Machine Intelligence and Emerging Technologies, MIET 2022, hosted by Noakhali Science and Technology University, Noakhali, Bangladesh, during September 23–25, 2022. The 104 papers presented in the proceedings were carefully reviewed and selected from 272 submissions. This book focuses on theoretical, practical, state-of-art applications, and research challenges in the field of artificial intelligence and emerging technologies. It will be helpful for active researchers and practitioners in this field. These papers are organized in the following topical sections: imaging for disease detection; pattern recognition and natural language processing; bio signals and recommendation systems for wellbeing; network, security and nanotechnology; and emerging technologies for society and industry.
Author: Simon Elias Bibri
Publisher: Springer
ISBN: 3319739816
Category : Political Science
Languages : en
Pages : 685
Get Book Here
Book Description
This book is intended to help explore the field of smart sustainable cities in its complexity, heterogeneity, and breadth, the many faces of a topical subject of major importance for the future that encompasses so much of modern urban life in an increasingly computerized and urbanized world. Indeed, sustainable urban development is currently at the center of debate in light of several ICT visions becoming achievable and deployable computing paradigms, and shaping the way cities will evolve in the future and thus tackle complex challenges. This book integrates computer science, data science, complexity science, sustainability science, system thinking, and urban planning and design. As such, it contains innovative computer–based and data–analytic research on smart sustainable cities as complex and dynamic systems. It provides applied theoretical contributions fostering a better understanding of such systems and the synergistic relationships between the underlying physical and informational landscapes. It offers contributions pertaining to the ongoing development of computer–based and data science technologies for the processing, analysis, management, modeling, and simulation of big and context data and the associated applicability to urban systems that will advance different aspects of sustainability. This book seeks to explicitly bring together the smart city and sustainable city endeavors, and to focus on big data analytics and context-aware computing specifically. In doing so, it amalgamates the design concepts and planning principles of sustainable urban forms with the novel applications of ICT of ubiquitous computing to primarily advance sustainability. Its strength lies in combining big data and context–aware technologies and their novel applications for the sheer purpose of harnessing and leveraging the disruptive and synergetic effects of ICT on forms of city planning that are required for future forms of sustainable development. This is because the effects of such technologies reinforce one another as to their efforts for transforming urban life in a sustainable way by integrating data–centric and context–aware solutions for enhancing urban systems and facilitating coordination among urban domains. This timely and comprehensive book is aimed at a wide audience across science, academia industry, and policymaking. It provides the necessary material to inform relevant research communities of the state–of–the–art research and the latest development in the area of smart sustainable urban development, as well as a valuable reference for planners, designers, strategists, and ICT experts who are working towards the development and implementation of smart sustainable cities based on big data analytics and context–aware computing.
Author: Khosrow-Pour, D.B.A., Mehdi
Publisher: IGI Global
ISBN: 1522575995
Category : Computers
Languages : en
Pages : 1946
Get Book Here
Book Description
From cloud computing to data analytics, society stores vast supplies of information through wireless networks and mobile computing. As organizations are becoming increasingly more wireless, ensuring the security and seamless function of electronic gadgets while creating a strong network is imperative. Advanced Methodologies and Technologies in Network Architecture, Mobile Computing, and Data Analytics highlights the challenges associated with creating a strong network architecture in a perpetually online society. Readers will learn various methods in building a seamless mobile computing option and the most effective means of analyzing big data. This book is an important resource for information technology professionals, software developers, data analysts, graduate-level students, researchers, computer engineers, and IT specialists seeking modern information on emerging methods in data mining, information technology, and wireless networks.
Author: Pradeep Kumar Mallick
Publisher: Springer Nature
ISBN: 9811514518
Category : Technology & Engineering
Languages : en
Pages : 685
Get Book Here
Book Description
The book presents new approaches and methods for solving real-world problems. It highlights, in particular, innovative research in the fields of Cognitive Informatics, Cognitive Computing, Computational Intelligence, Advanced Computing, and Hybrid Intelligent Models and Applications. New algorithms and methods in a variety of fields are presented, together with solution-based approaches. The topics addressed include various theoretical aspects and applications of Computer Science, Artificial Intelligence, Cybernetics, Automation Control Theory, and Software Engineering.
Author: Iqbal H. Sarker
Publisher: Springer Nature
ISBN: 3031544978
Category :
Languages : en
Pages : 207
Get Book Here
Book Description
Author: Teresa Guarda
Publisher: Springer Nature
ISBN: 3031488555
Category : Computers
Languages : en
Pages : 470
Get Book Here
Book Description
The three-volume set CCIS 1935, 1936 and 1937 constitutes the refereed post-conference proceedings of the Third International Conference, ARTIIS 2023, Madrid, Spain, October 18–20, 2023, Proceedings. The 98 revised full papers presented in these proceedings were carefully reviewed and selected from 297 submissions. The papers are organized in the following topical sections: Part I: Computing Solutions, Data Intelligence Part II: Sustainability, Ethics, Security, and Privacy Part III: Applications of Computational Mathematics to Simulation and Data Analysis (ACMaSDA 2023), Challenges and the Impact of Communication and Information Technologies on Education (CICITE 2023), Workshop on Gamification Application and Technologies (GAT 2023), Bridging Knowledge in a Fragmented World (glossaLAB 2023), Intelligent Systems for Health and Medical Care (ISHMC 2023), Intelligent Systems for Health and Medical Care (ISHMC 2023), Intelligent Systems in Forensic Engineering (ISIFE 2023), International Symposium on Technological Innovations for Industry and Soci-ety (ISTIIS 2023), International Workshop on Electronic and Telecommunications (IWET 2023), Innovation in Educational Technology (JIUTE 2023), Smart Tourism and Information Systems (SMARTTIS 2023).
Author: Sachi Nandan Mohanty
Publisher: John Wiley & Sons
ISBN: 1119785855
Category : Computers
Languages : en
Pages : 528
Get Book Here
Book Description
Machine Learning Approach for Cloud Data Analytics in IoT The book covers the multidimensional perspective of machine learning through the perspective of cloud computing and Internet of Things ranging from fundamentals to advanced applications Sustainable computing paradigms like cloud and fog are capable of handling issues related to performance, storage and processing, maintenance, security, efficiency, integration, cost, energy and latency in an expeditious manner. In order to expedite decision-making involved in the complex computation and processing of collected data, IoT devices are connected to the cloud or fog environment. Since machine learning as a service provides the best support in business intelligence, organizations have been making significant investments in this technology. Machine Learning Approach for Cloud Data Analytics in IoT elucidates some of the best practices and their respective outcomes in cloud and fog computing environments. It focuses on all the various research issues related to big data storage and analysis, large-scale data processing, knowledge discovery and knowledge management, computational intelligence, data security and privacy, data representation and visualization, and data analytics. The featured technologies presented in the book optimizes various industry processes using business intelligence in engineering and technology. Light is also shed on cloud-based embedded software development practices to integrate complex machines so as to increase productivity and reduce operational costs. The various practices of data science and analytics which are used in all sectors to understand big data and analyze massive data patterns are also detailed in the book.
