Context Aware Machine Learning And Mobile Data Analytics

Author : Iqbal Sarker,Alan Colman,Jun Han,Paul Watters
Publisher : Springer Nature
Page : 164 pages
File Size : 43,5 Mb
Release : 2022-01-01
Category : Computers
ISBN : 9783030885304

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Context-Aware Machine Learning and Mobile Data Analytics by Iqbal Sarker,Alan Colman,Jun Han,Paul Watters Pdf

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 : Martin Atzmueller,Alvin Chin,Frederik Janssen,Immanuel Schweizer,Christoph Trattner
Publisher : Springer
Page : 187 pages
File Size : 43,8 Mb
Release : 2016-01-06
Category : Computers
ISBN : 9783319290096

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Big Data Analytics in the Social and Ubiquitous Context by Martin Atzmueller,Alvin Chin,Frederik Janssen,Immanuel Schweizer,Christoph Trattner Pdf

The 9 papers presented in this book are revised and significantly extended versions of papers submitted to three related workshops: The 5th International Workshop on Mining Ubiquitous and Social Environments, MUSE 2014, and the First International Workshop on Machine Learning for Urban Sensor Data, SenseML 2014, which were held on September 15, 2014, in conjunction with the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2014) in Nancy, France; and the 5th International Workshop on Modeling Social Media (MSM 2014) that was held on April 8, 2014 in conjunction with ACM WWW in Seoul, Korea.

Author : Tom Lovett,Eamonn O'Neill
Publisher : Springer Science & Business Media
Page : 193 pages
File Size : 43,8 Mb
Release : 2012-04-23
Category : Computers
ISBN : 9780857296252

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Mobile Context Awareness by Tom Lovett,Eamonn O'Neill Pdf

Mobile context-awareness is a popular research trend in the field of ubiquitous computing. Advances in mobile device sensory hardware and the rise of ‘virtual’ sensors such as web application programming interfaces (APIs) mean that the mobile user is exposed to a vast range of data that can be used for new advanced applications. Mobile Context Awareness presents work from industrial and academic researchers, focusing on novel methods of context acquisition in the mobile environment – particularly through the use of physical and virtual sensors – along with research into new applications utilising this context. In addition, the book provides insights into the technical and usability challenges involved in mobile context-awareness, as well as observations on current and future trends in the field.

Author : Fa-Long Luo
Publisher : John Wiley & Sons
Page : 490 pages
File Size : 48,9 Mb
Release : 2020-02-10
Category : Technology & Engineering
ISBN : 9781119562252

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Machine Learning for Future Wireless Communications by Fa-Long Luo Pdf

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 : Nilanjan Dey,Sanjeev Wagh,Parikshit N. Mahalle,Mohd. Shafi Pathan
Publisher : CRC Press
Page : 225 pages
File Size : 54,6 Mb
Release : 2019-05-20
Category : Computers
ISBN : 9780429804571

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Applied Machine Learning for Smart Data Analysis by Nilanjan Dey,Sanjeev Wagh,Parikshit N. Mahalle,Mohd. Shafi Pathan Pdf

The book focuses on how machine learning and the Internet of Things (IoT) has empowered the advancement of information driven arrangements including key concepts and advancements. Ontologies that are used in heterogeneous IoT environments have been discussed including interpretation, context awareness, analyzing various data sources, machine learning algorithms and intelligent services and applications. Further, it includes unsupervised and semi-supervised machine learning techniques with study of semantic analysis and thorough analysis of reviews. Divided into sections such as machine learning, security, IoT and data mining, the concepts are explained with practical implementation including results. Key Features Follows an algorithmic approach for data analysis in machine learning Introduces machine learning methods in applications Address the emerging issues in computing such as deep learning, machine learning, Internet of Things and data analytics Focuses on machine learning techniques namely unsupervised and semi-supervised for unseen and seen data sets Case studies are covered relating to human health, transportation and Internet applications

Author : Bader Alyoubi,Chiheb-Eddine Ben Ncir,Ibraheem Alharbi,Anis Jarboui
Publisher : Springer Nature
Page : 214 pages
File Size : 40,5 Mb
Release : 2022-12-15
Category : Technology & Engineering
ISBN : 9783031184833

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Machine Learning and Data Analytics for Solving Business Problems by Bader Alyoubi,Chiheb-Eddine Ben Ncir,Ibraheem Alharbi,Anis Jarboui Pdf

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,Mohammad Ali Moni,M. Shamim Kaiser,Mohammad Shamsul Arefin
Publisher : Springer Nature
Page : 597 pages
File Size : 40,5 Mb
Release : 2023-06-10
Category : Computers
ISBN : 9783031346194

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Machine Intelligence and Emerging Technologies by Md. Shahriare Satu,Mohammad Ali Moni,M. Shamim Kaiser,Mohammad Shamsul Arefin Pdf

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 : Khosrow-Pour, D.B.A., Mehdi
Publisher : IGI Global
Page : 1857 pages
File Size : 55,7 Mb
Release : 2018-10-19
Category : Computers
ISBN : 9781522575993

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Advanced Methodologies and Technologies in Network Architecture, Mobile Computing, and Data Analytics by Khosrow-Pour, D.B.A., Mehdi Pdf

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 : Iqbal H. Sarker
Publisher : Springer Nature
Page : 207 pages
File Size : 48,5 Mb
Release : 2024-06-29
Category : Electronic
ISBN : 9783031544972

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AI-Driven Cybersecurity andThreat Intelligence by Iqbal H. Sarker Pdf

Author : Teresa Guarda,Filipe Portela,Jose Maria Diaz-Nafria
Publisher : Springer Nature
Page : 470 pages
File Size : 41,6 Mb
Release : 2024-01-02
Category : Computers
ISBN : 9783031488559

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Advanced Research in Technologies, Information, Innovation and Sustainability by Teresa Guarda,Filipe Portela,Jose Maria Diaz-Nafria Pdf

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 : Judith S. Hurwitz,Marcia Kaufman,Adrian Bowles
Publisher : John Wiley & Sons
Page : 288 pages
File Size : 51,5 Mb
Release : 2015-02-12
Category : Computers
ISBN : 9781118896631

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Cognitive Computing and Big Data Analytics by Judith S. Hurwitz,Marcia Kaufman,Adrian Bowles Pdf

A comprehensive guide to learning technologies that unlock the value in big data Cognitive Computing provides detailed guidance toward building a new class of systems that learn from experience and derive insights to unlock the value of big data. This book helps technologists understand cognitive computing's underlying technologies, from knowledge representation techniques and natural language processing algorithms to dynamic learning approaches based on accumulated evidence, rather than reprogramming. Detailed case examples from the financial, healthcare, and manufacturing walk readers step-by-step through the design and testing of cognitive systems, and expert perspectives from organizations such as Cleveland Clinic, Memorial Sloan-Kettering, as well as commercial vendors that are creating solutions. These organizations provide insight into the real-world implementation of cognitive computing systems. The IBM Watson cognitive computing platform is described in a detailed chapter because of its significance in helping to define this emerging market. In addition, the book includes implementations of emerging projects from Qualcomm, Hitachi, Google and Amazon. Today's cognitive computing solutions build on established concepts from artificial intelligence, natural language processing, ontologies, and leverage advances in big data management and analytics. They foreshadow an intelligent infrastructure that enables a new generation of customer and context-aware smart applications in all industries. Cognitive Computing is a comprehensive guide to the subject, providing both the theoretical and practical guidance technologists need. Discover how cognitive computing evolved from promise to reality Learn the elements that make up a cognitive computing system Understand the groundbreaking hardware and software technologies behind cognitive computing Learn to evaluate your own application portfolio to find the best candidates for pilot projects Leverage cognitive computing capabilities to transform the organization Cognitive systems are rightly being hailed as the new era of computing. Learn how these technologies enable emerging firms to compete with entrenched giants, and forward-thinking established firms to disrupt their industries. Professionals who currently work with big data and analytics will see how cognitive computing builds on their foundation, and creates new opportunities. Cognitive Computing provides complete guidance to this new level of human-machine interaction.

Author : Simon Elias Bibri
Publisher : Springer
Page : 660 pages
File Size : 49,9 Mb
Release : 2018-02-24
Category : Political Science
ISBN : 9783319739816

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Smart Sustainable Cities of the Future by Simon Elias Bibri Pdf

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 : Mohd. Shafi Pathan
Publisher : CRC Press
Page : 225 pages
File Size : 43,6 Mb
Release : 2019
Category : Computers
ISBN : 0429440952

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Applied Machine Learning for Smart Data Analysis by Mohd. Shafi Pathan Pdf

The book focuses on how machine learning and the Internet of Things (IoT) has empowered the advancement of information driven arrangements including key concepts and advancements. Ontologies that are used in heterogeneous IoT environments have been discussed including interpretation, context awareness, analyzing various data sources, machine learning algorithms and intelligent services and applications. Further, it includes unsupervised and semi-supervised machine learning techniques with study of semantic analysis and thorough analysis of reviews. Divided into sections such as machine learning, security, IoT and data mining, the concepts are explained with practical implementation including results. Key Features Follows an algorithmic approach for data analysis in machine learning Introduces machine learning methods in applications Address the emerging issues in computing such as deep learning, machine learning, Internet of Things and data analytics Focuses on machine learning techniques namely unsupervised and semi-supervised for unseen and seen data sets Case studies are covered relating to human health, transportation and Internet applications

Author : Ajith Abraham,Thomas Hanne,Oscar Castillo,Niketa Gandhi,Tatiane Nogueira Rios,Tzung-Pei Hong
Publisher : Springer Nature
Page : 817 pages
File Size : 42,8 Mb
Release : 2021-04-16
Category : Technology & Engineering
ISBN : 9783030730505

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Hybrid Intelligent Systems by Ajith Abraham,Thomas Hanne,Oscar Castillo,Niketa Gandhi,Tatiane Nogueira Rios,Tzung-Pei Hong Pdf

This book highlights the recent research on hybrid intelligent systems and their various practical applications. It presents 58 selected papers from the 20th International Conference on Hybrid Intelligent Systems (HIS 2020) and 20 papers from the 12th World Congress on Nature and Biologically Inspired Computing (NaBIC 2020), which was held online, from December 14 to 16, 2020. A premier conference in the field of artificial intelligence, HIS - NaBIC 2020 brought together researchers, engineers and practitioners whose work involves intelligent systems, network security and their applications in industry. Including contributions by authors from 25 countries, the book offers a valuable reference guide for all researchers, students and practitioners in the fields of science and engineering.

Author : Dominik Ryzko
Publisher : John Wiley & Sons
Page : 208 pages
File Size : 45,8 Mb
Release : 2020-03-31
Category : Computers
ISBN : 9781119597841

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Modern Big Data Architectures by Dominik Ryzko Pdf

Provides an up-to-date analysis of big data and multi-agent systems The term Big Data refers to the cases, where data sets are too large or too complex for traditional data-processing software. With the spread of new concepts such as Edge Computing or the Internet of Things, production, processing and consumption of this data becomes more and more distributed. As a result, applications increasingly require multiple agents that can work together. A multi-agent system (MAS) is a self-organized computer system that comprises multiple intelligent agents interacting to solve problems that are beyond the capacities of individual agents. Modern Big Data Architectures examines modern concepts and architecture for Big Data processing and analytics. This unique, up-to-date volume provides joint analysis of big data and multi-agent systems, with emphasis on distributed, intelligent processing of very large data sets. Each chapter contains practical examples and detailed solutions suitable for a wide variety of applications. The author, an internationally-recognized expert in Big Data and distributed Artificial Intelligence, demonstrates how base concepts such as agent, actor, and micro-service have reached a point of convergence—enabling next generation systems to be built by incorporating the best aspects of the field. This book: Illustrates how data sets are produced and how they can be utilized in various areas of industry and science Explains how to apply common computational models and state-of-the-art architectures to process Big Data tasks Discusses current and emerging Big Data applications of Artificial Intelligence Modern Big Data Architectures: A Multi-Agent Systems Perspective is a timely and important resource for data science professionals and students involved in Big Data analytics, and machine and artificial learning.