Expert systems / knowledge-based systems

This book focuses on data and how modern business firms use social data, specifically Online Social Networks (OSNs) incorporated as part of the infrastructure for a number of emerging applications such as personalized recommendation systems, opinion analysis, expertise retrieval, and computational advertising.

This book sets the stage of the evolution of corporate governance, laws and regulations, other forms of governance, and the interaction between data governance and other corporate governance sub-disciplines.

This book provides an in-depth analysis of the current evolutionary clustering techniques.

This book comprises the best deliberations with the theme "e;Machine Learning Technologies and Applications"e; in the "e;International Conference on Advances in Computer Engineering and Communication Systems (ICACECS 2020),"e; organized by the Department of Computer Science and Engineering, VNR Vignana Jyothi Institute of Engineering and Technology.

This book contains revised and extended research articles written by prominent researchers, selected from presentations at the International MultiConference of Engineers and Computer Scientists (IMECS 2018) held in Hong Kong, 14-16 March, 2018.

This book provides a comprehensive introduction to rough set-based feature selection.

Data Mining is the science and technology of exploring data in order to discover previously unknown patterns.

This book systematically analyses the latest insights into night vision imaging processing and perceptual understanding as well as related theories and methods.

The book features original papers from International Conference on Computational Methods and Data Engineering (ICCMDE 2021), organized by School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India, during November 25-26, 2021.

This book presents Proceedings of the International Conference on Intelligent Systems and Networks (ICISN 2022), held at Hanoi in Vietnam.

In the big data era, increasing information can be extracted from the same source object or scene.

This book highlights an innovative approach for extracting terminological cores from subject domain-bounded collections of professional texts.

This book provides a comprehensive overview of network behavior analysis that mines Internet traffic data in order to extract, model, and make sense of behavioral patterns in Internet "e;objects"e; such as end hosts, smartphones, Internet of things, and applications.

Machine learning (ML) has become a commonplace element in our everyday lives and a standard tool for many fields of science and engineering.

This book provides an overview of the history of integrative bioinformatics and the actual situation and the relevant tools.

Representation learning in heterogeneous graphs (HG) is intended to provide a meaningful vector representation for each node so as to facilitate downstream applications such as link prediction, personalized recommendation, node classification, etc.

Deep Learning models are at the core of artificial intelligence research today.

This book introduces readers to an evolutionary learning approach, specifically genetic programming (GP), for production scheduling.

This book provides an introduction to the field of periodic pattern mining, reviews state-of-the-art techniques, discusses recent advances, and reviews open-source software.

This book presents the data privacy protection which has been extensively applied in our current era of big data.

This book brings together two major trends: data science and blockchains.

Today, big data affects countless aspects of our daily lives.

This book delves into the concept of data as a critical enterprise asset needed for informed decision making, compliance, regulatory reporting and insights into trends, behaviors, performance and patterns.

This book presents the state of the art in distributed machine learning algorithms that are based on gradient optimization methods.

Graph data is powerful, thanks to its ability to model arbitrary relationship between objects and is encountered in a range of real-world applications in fields such as bioinformatics, traffic network, scientific collaboration, world wide web and social networks.

This book presents Proceedings of the International Conference on Intelligent Systems and Networks (ICISN 2021), held at Hanoi in Vietnam.

With the proliferation of GPS devices in daily life, trajectory data that records where and when people move is now readily available on a large scale.

This book focuses on using artificial intelligence (AI) to improve blockchain ecosystems.

This book discusses various aspects of text data mining.

This book enriches unsupervised outlier detection research by proposing several new distance-based and density-based outlier scores in a k-nearest neighbors' setting.

This book provides a comprehensive introduction to the application of artificial intelligence in social computing, from fundamental data processing to advanced social network computing.

This book gathers outstanding papers presented at the International Conference on Data Science and Applications (ICDSA 2019), held at Kautilya Institute of Technology and Engineering, Jaipur, Rajasthan, India, from 2 to 3 December 2019.

This book discusses the smooth integration of optical and RF networks in 5G and beyond (5G+) heterogeneous networks (HetNets), covering both planning and operational aspects.

This book comprehensively covers the topic of data science.

This book promotes a meaningful and appropriate dialogue and cross-disciplinary partnerships on Artificial Intelligence (AI) in governance and disaster management.

This book records the new research findings and development in the field of industrial engineering and engineering management, and it will serve as the guidebook for the potential development in future.

This book includes selected papers from the International Conference on Data Science and Intelligent Applications (ICDSIA 2020), hosted by Gandhinagar Institute of Technology (GIT), Gujarat, India, on January 24-25, 2020.

Deep reinforcement learning (DRL) is the combination of reinforcement learning (RL) and deep learning.

This book introduces readers to a workload-aware methodology for large-scale graph algorithm optimization in graph-computing systems, and proposes several optimization techniques that can enable these systems to handle advanced graph algorithms efficiently.

The book discusses machine learning-based decision-making models, and presents intelligent, hybrid and adaptive methods and tools for solving complex learning and decision-making problems under conditions of uncertainty.

This book occupies a unique position in the field of statistical analysis in the behavioural and social sciences in that it targets learners who would benefit from learning more conceptually and less computationally about statistical procedures and the software packages that can be used to implement them.

This book focuses on Web recommender systems, offering an overview of approaches to develop these state-of-the-art systems.

This book covers both theory and applications in the automation of software testing tools and techniques for various types of software (e.

Over the last decade, there has been a growing interest in human behavior analysis, motivated by societal needs such as security, natural interfaces, affective computing, and assisted living.

This book covers deep-learning-based approaches for sentiment analysis, a relatively new, but fast-growing research area, which has significantly changed in the past few years.

This book introduces research presented at the "e;International Conference on Artificial Intelligence: Advances and Applications-2019 (ICAIAA 2019),"e; a two-day conference and workshop bringing together leading academicians, researchers as well as students to share their experiences and findings on all aspects of engineering applications of artificial intelligence.

This book includes high-quality papers presented at the International Conference on Data Science and Management (ICDSM 2019), organised by the Gandhi Institute for Education and Technology, Bhubaneswar, from 22 to 23 February 2019.

This book explores the possibility of using social media data for detecting socio-economic recovery activities.

This book gathers a collection of high-quality peer-reviewed research papers presented at the 2nd International Conference on Data and Information Sciences (ICDIS 2019), held at Raja Balwant Singh Engineering Technical Campus, Agra, India, on March 29-30, 2019.

This book offers a broad and structured overview of the state-of-the-art methods that could be applied for context-dependent languages like Arabic.