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Data mining analysis techniques have undergone significant developments in recent years. This has led to improved uses throughout numerous functions and applications. Intelligent Multidimensional Data Clustering and Analysis is an authoritative reference source for the latest scholarly research on the advantages and challenges presented by the use of cluster analysis techniques. Highlighting theoretical foundations, computing paradigms, and real-world applications, this book is ideally designed for researchers, practitioners, upper-level students, and professionals interested in the latest developments in cluster analysis for large data sets.
As the most natural and convenient means of conveying or transmitting information, images play a vital role in our daily lives. Image processing is now of paramount importance in the computer vision research community, and proper processing of two-dimensional (2D) real-life images plays a key role in many real-life applications as well as commercial developments. Intelligent Multidimensional Data and Image Processing is a vital research publication that contains an in-depth exploration of image processing techniques used in various applications, including how to handle noise removal, object segmentation, object extraction, and the determination of the nearest object classification and its associated confidence level. Featuring coverage on a broad range of topics such as object detection, machine vision, and image conversion, this book provides critical research for scientists, computer engineers, professionals, researchers, and academicians seeking current research on solutions for new challenges in 2D and 3D image processing.
Understanding the social relations within the fields of business and economics is vital for the promotion of success within a certain organization. Analytics and statistics have taken a prominent role in marketing and management practices as professionals are constantly searching for a competitive advantage. Converging these technological tools with traditional methods of business relations is a trending area of research. Applied Social Network Analysis With R: Emerging Research and Opportunities is an essential reference source that materializes and analyzes the issue of structure in terms of its effects on human societies and the state of the individuals in these communities. Even though the theme of the book is business-oriented, an approach underlining and strengthening the ties of this field of study with social sciences for further development is adopted throughout. Therefore, the knowledge presented is valid for analyzing not only the organization of the business world but also for the organization of any given community. Featuring research on topics such as network visualization, graph theory, and micro-dynamics, this book is ideally designed for researchers, practitioners, business professionals, managers, programmers, academicians, and students seeking coverage on analyzing social and business networks using modern methods of statistics, programming, and data sets.
This book gathers papers addressing state-of-the-art research in all areas of information and communication technologies and their applications in intelligent computing, cloud storage, data mining and software analysis. It presents the outcomes of the Sixth International Conference on Information and Communication Technology for Intelligent Systems (ICTIS 2022), held in Ahmedabad, India. The book is divided into two volumes. It discusses the fundamentals of various data analysis techniques and algorithms, making it a valuable resource for researchers and practitioners alike.
Autism spectrum disorder (ASD) is known as a neuro-disorder in which a person may face problems in interaction and communication with people, amongst other challenges. As per medical experts, ASD can be diagnosed at any stage or age but is often noticeable within the first two years of life. If caught early enough, therapies and services can be provided at this early stage instead of waiting until it is too late. ASD occurrences appear to have increased over the last couple of years leading to the need for more research in the field. It is crucial to provide researchers and clinicians with the most up-to-date information on the clinical features, etiopathogenesis, and therapeutic strategies for patients as well as to shed light on the other psychiatric conditions often associated with ASD. In addition, it is equally important to understand how to detect ASD in individuals for accurate diagnosing and early detection. Artificial Intelligence for Accurate Analysis and Detection of Autism Spectrum Disorder discusses the early detection and diagnosis of autism spectrum disorder enabled by artificial intelligence technologies, applications, and therapies. This book will focus on the early diagnosis of ASD through artificial intelligence, such as deep learning and machine learning algorithms, for confirming diagnosis or suggesting the need for further evaluation of individuals. The chapters will also discuss the use of artificial intelligence technologies, such as medical robots, for enhancing the communication skills and the social and emotional skills of children who have been diagnosed with ASD. This book is ideally intended for IT specialists, data scientists, academicians, scholars, researchers, policymakers, medical practitioners, and students interested in how artificial intelligence is impacting the diagnosis and treatment of autism spectrum disorder.
The Internet of Things has become a major influence on the development of new technologies and innovations. When combined with smart services, the end-user experience can be significantly enhanced. Novel Design and the Applications of Smart-M3 Platform in the Internet of Things: Emerging Research and Opportunities provides an innovative outlook on the development of open source technology for the creation of smart spaces and services. Including a range of relevant topics such as interoperability, system architecture, and information processing, this book is an ideal reference source for academics, researchers, graduate students, and practitioners interested in the latest advancements in the Internet of Things.
Text analysis tools aid in extracting meaning from digital content. As digital text becomes more and more complex, new techniques are needed to understand conceptual structure. Concept Parsing Algorithms (CPA) for Textual Analysis and Discovery: Emerging Research and Opportunities provides an innovative perspective on the application of algorithmic tools to study unstructured digital content. Highlighting pertinent topics such as semantic tools, semiotic systems, and pattern detection, this book is ideally designed for researchers, academics, students, professionals, and practitioners interested in developing a better understanding of digital text analysis.
The main problems that prevent fast and high-quality document processing in electronic document management systems are insufficient and unstructured information, information redundancy, and the presence of large amounts of undesirable user information. The human factor has a significant impact on the efficiency of document search. An average user is not aware of the advanced option of a query language and uses typical queries. Development of a specialized software toolkit intended for information systems and electronic document management systems can be an effective solution of the tasks listed above. Such toolkits should be based on the means and methods of automatic keyword extraction and text classification. The categorization (or classification) of texts into predefined categories has witnessed a booming interest in the last 10 years due to the increased availability of documents in digital form and the ensuing need to organize them. Thus, research on keyword extraction, advancements in the field, and possible future solutions is of great importance in current times. Developing a Keyword Extractor and Document Classifier: Emerging Research and Opportunities presents an information extraction mechanism that can process many kinds of inputs, realize the type of text, and understand the percentage of the keywords that has to be stored. This mechanism then supports information extraction and information categorization mechanisms. This module is used to support a text summarization mechanism, which leads—with the help of the keyword extraction module—to text categorization. It employs lexical and information retrieval techniques to extract phrases from the document text that are likely to characterize it and determines the category of the retrieved text to present a summary to the users. This book is ideal for practitioners, stakeholders, researchers, academicians, and students who are interested in the development of a new keyword extractor and document classifier method.
Continuous improvements in data analysis and cloud computing have allowed more opportunities to develop systems with user-focused designs. This not only leads to higher success in day-to-day usage, but it increases the overall probability of technology adoption. Advancing Cloud Database Systems and Capacity Planning With Dynamic Applications is a key resource on the latest innovations in cloud database systems and their impact on the daily lives of people in modern society. Highlighting multidisciplinary studies on information storage and retrieval, big data architectures, and artificial intelligence, this publication is an ideal reference source for academicians, researchers, scientists, advanced level students, technology developers and IT officials.
Healthcare and pharmaceuticals are rapidly advancing with technological innovations, and the lack of understanding of AI algorithms poses a significant challenge in these fields. The need for more transparency in AI decision-making processes raises concerns about accountability, ethical implications, and regulatory compliance. As stakeholders in these critical sectors seek clarity and understanding, Analyzing Explainable AI in Healthcare and the Pharmaceutical Industry provides a reliable resource to discover new solutions. This book serves as a comprehensive guide, unraveling the complexities of explainable artificial intelligence (XAI) and its pivotal role in transforming healthcare and pharmaceutical practices. Demystifying AI algorithms and revealing their decision-making mechanisms equips readers with the foundational knowledge needed to confidently navigate AI integration in these domains. From healthcare professionals to policymakers, its insights cater to a diverse audience, fostering cross-disciplinary collaboration and facilitating informed decision-making.