Catalogue Search | MBRL
Are you sure you want to remove the book from the shelf?
{{itemTitle}}
4,451
result(s) for
"Expert systems (Computer science)"
Sort by:
Mobile Data Science and Intelligent Apps: Concepts, AI-Based Modeling and Research Directions
Artificial intelligence (AI) techniques have grown rapidly in recent years in the context of computing with smart mobile phones that typically allows the devices to function in an intelligent manner. Popular AI techniques include machine learning and deep learning methods, natural language processing, as well as knowledge representation and expert systems, can be used to make the target mobile applications intelligent and more effective. In this paper, we present a comprehensive view on “mobile data science and intelligent apps” in terms of concepts and AI-based modeling that can be used to design and develop intelligent mobile applications for the betterment of human life in their diverse day-to-day situation. This study also includes the concepts and insights of various AI-powered intelligent apps in several application domains, ranging from personalized recommendation to healthcare services, including COVID-19 pandemic management in recent days. Finally, we highlight several research issues and future directions relevant to our analysis in the area of mobile data science and intelligent apps. Overall, this paper aims to serve as a reference point and guidelines for the mobile application developers as well as the researchers in this domain, particularly from the technical point of view.
Journal Article
Research advances in intelligent computing
\"Since the invention of computers or machines, scientists and researchers are trying very hard to enhance their capabilities to perform various tasks. As a consequence, the capabilities of computers are growing exponentially day by day in terms of diverse working domains, versatile jobs, processing speed, and reduced size. Now, we are in the race to make the computers or machines as intelligent as human beings. Artificial Intelligence (AI) came up as a way of making a computer or computer software think in the similar manner the intelligent humans think. AI is inspired by the study of human brain like how humans think, learn, decide and act while trying to solve a problem. The outcomes of this study are the basis of developing intelligent software and systems or Intelligent Computing (IC). An IC system has the capability of reasoning, learning, problem solving, perception, and linguistic intelligence. The IC systems consist of AI techniques as well as other emerging techniques that make a system intelligent. The use of intelligent computing has been seen in almost every sub-domain of computer science such as networking, software engineering, gaming, natural language processing, computer vision, image processing, data science, robotics, expert systems, and security. Now a days, the use of IC can also be seen for solving various complex problems in diverse domains such as for predicting disease in medical science, predicting land fertility or crop productivity in agriculture science, predicting market growth in economics, weather forecasting and so on. For all these reasons, this book presents the advances in AI techniques, under the umbrella of IC. In this context, the book includes the recent research works have been done in the areas of machine learning, neural networks, deep learning, evolutionary algorithms, genetic algorithms, swarm intelligence, fuzzy systems and so on. This book provides theoretical, algorithmic, simulation, and implementation-based recent research advancements related to the Intelligent Computing\"-- Provided by publisher.
Book
Blockchain basics : a non-technical introduction in 25 steps
In 25 concise steps, you will learn the basics of blockchain technology. No mathematical formulas, program code, or computer science jargon are used. No previous knowledge in computer science, mathematics, programming, or cryptography is required. Terminology is explained through pictures, analogies, and metaphors.This book bridges the gap that exists between purely technical books about the blockchain and purely business-focused books. It does so by explaining both the technical concepts that make up the blockchain and their role in business-relevant applications.What You'll LearnWhat the blockchain isWhy it is needed and what problem it solvesWhy there is so much excitement about the blockchain and its potentialMajor components and their purposeHow various components of the blockchain work and interactLimitations, why they exist, and what has been done to overcome themMajor application scenariosWho This Book Is ForEveryone who wants to get a general idea of what blockchain technology is, how it works, and how it will potentially change the financial system as we know it
eBook
Granular Computing
Granular computing focuses on formalizing information granules and unifying them to create a coherent methodological and developmental environment for intelligent system design and analysis. This innovative book presents the unified principles of granular computing along with its comprehensive algorithmic framework and design practices. It explores key concepts and formalisms as well as applications. It also emphasizes the need to consider information granularity as an important design asset that helps in the construction of more realistic models of real-world systems and in facilitating collaborative pursuits of system modeling.
eBook
Smart and intelligent systems : the human elements in artificial intelligence, robotics, and cybersecurity
\"This book is perfect for engineering students in data sciences, artificial intelligence, practitioners at all levels in the field of human factors and ergonomics, systems engineering, computer science, software engineering and robotics\"-- Provided by publisher.
Book
A systematic review and taxonomy of explanations in decision support and recommender systems
With the recent advances in the field of artificial intelligence, an increasing number of decision-making tasks are delegated to software systems. A key requirement for the success and adoption of such systems is that users must trust system choices or even fully automated decisions. To achieve this, explanation facilities have been widely investigated as a means of establishing trust in these systems since the early years of expert systems. With today’s increasingly sophisticated machine learning algorithms, new challenges in the context of explanations, accountability, and trust towards such systems constantly arise. In this work, we systematically review the literature on explanations in advice-giving systems. This is a family of systems that includes recommender systems, which is one of the most successful classes of advice-giving software in practice. We investigate the purposes of explanations as well as how they are generated, presented to users, and evaluated. As a result, we derive a novel comprehensive taxonomy of aspects to be considered when designing explanation facilities for current and future decision support systems. The taxonomy includes a variety of different facets, such as explanation objective, responsiveness, content and presentation. Moreover, we identified several challenges that remain unaddressed so far, for example related to fine-grained issues associated with the presentation of explanations and how explanation facilities are evaluated.
Journal Article
Managing knowledge networks
\"The information context of the modern organization is rapidly evolving in the face of intense global competition. Information technologies, including databases, new telecommunications systems, and software for synthesizing information, make a vast array of information available to an ever expanding number of organizational members. Management's exclusive control over knowledge is steadily declining, in part because of the downsizing of organizations and the decline of the number of layers in an organizational hierarchy. These trends, as well as issues surrounding the Web 2.0 and social networking, mean that it is increasingly important that we understand how informal knowledge networks impact the generation, capturing, storing, dissemination, and application of knowledge. This innovative book provides a thorough analysis of knowledge networks, focusing on how relationships contribute to the creation of knowledge, its distribution within organizations, how it is diffused and transferred, and how people find it and share it collaboratively\"--Provided by publisher.
Book
Fuzzy expert systems and fuzzy reasoning
Fuzzy sets were for a long time not accepted by the AI community. Now they have become highly evolved and their techniques are well established. This book will teach the reader how to construct a fuzzy expert system to solve real-world problems. After a general discussion of expert systems, the basic fuzzy math required is presented first, requiring little more math background than high-school algebra. This book will fill a void in the market because although there are many books on expert systems, none devote more than a few pages to the notion of fuzzy sets and their applications in this domain. Therefore their use in this book is timely and should be well received. The book is designed as a text and has ample problems with solutions, a solutions manual and an accompanying program on our ftp site. Coverage is accessible to practitioners and academic readers alike.
eBook