Philippe Fournier-Viger – författare

This book presents an overview of techniques for discovering high-utility patterns (patterns with a high importance) in data. It introduces the main types of high-utility patterns, as well as the theory and core algorithms for high-utility pattern mining, and describes recent advances, applications, open-source software, and research opportunities. It also discusses several types of discrete data, including customer transaction data and sequential data.

The 25 papers presented in this volume were carefully reviewed and selected from 53 submissions. The papers are organized in topical sections named: big data analytics: vision and perspectives; search and information extraction; predictive analytics in medical and agricultural domains; graph analytics; pattern mining; and machine learning.

This book constitutes the thoroughly refereed proceedings of the 33rd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2020, held in Kitakyushu, Japan, in September 2020.

The 62 full papers and 17 short papers presented were carefully reviewed and selected from 119 submissions. The IEA/AIE 2020 conference will continue the tradition of emphasizing on applications of applied intelligent systems to solve real-life problems in all areas. These areas include are language processing; robotics and drones; knowledge based systems; innovative applications of intelligent systems; industrial applications; networking applications; social network analysis; financial applications and blockchain; medical and health-related applications; anomaly detection and automated diagnosis; decision-support and agent-based systems; multimedia applications; machine learning; data management and data clustering; pattern mining; system control, classification, and fault diagnosis.

The book will be an excellent starting point for postgraduate students and researchers because each chapter is design to have future research directions.

This book presents an overview of how machine learning and data mining techniques are used for tracking and preventing diseases. It covers several aspects such as stress level identification of a person from his/her speech, automatic diagnosis of disease from X-ray images, intelligent diagnosis of Glaucoma from clinical eye examination data, prediction of protein-coding genes from big genome data, disease detection through microscopic analysis of blood cells, information retrieval from electronic medical record using named entity recognition approaches, and prediction of drug-target interactions.

The book is suitable for computer scientists having a bachelor degree in computer science. The book is an ideal resource as a reference book for teaching a graduate course on AI for Medicine or AI for Health care. Researchers working in the multidisciplinary areas use this book to discover the current developments. Besides itsuse in academia, this book provides enough details about the state-of-the-art algorithms addressing various biomedical domains, so that it could be used by industry practitioners who want to implement AI techniques to analyze the diseases. Medical institutions use this book as reference material and give tutorials to medical experts on how the advanced AI and ML techniques contribute to the diagnosis and prediction of the diseases.

This book constitutes the thoroughly refereed proceedings of the 35th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2022, held in Kitakyushu, Japan, in July 2022.

The 67 full papers and 11 short papers presented were carefully reviewed and selected from 127 submissions. The IEA/AIE 2022 conference focuses on focuses on applications of applied intelligent systems to solve real-life problems in all areas including business and finance, science, engineering, industry, cyberspace, bioinformatics, automation, robotics, medicine and biomedicine, and human-machine interactions.

This book constitutes the refereed proceedings of the 11th International Conference on Model and Data Engineering, MEDI 2022, held in Cairo, Egypt, in November 2022. The 18 full papers presented in this book were carefully reviewed and selected from 65 submissions. The papers cover topics such as database systems, data stream analysis, knowledge-graphs, machine learning, model-driven engineering, image processing, diagnosis, natural language processing, optimization, and advanced applications such as the internet of things and healthcare.

The first chapter is an introduction to pattern mining and periodic pattern mining. The concepts of periodicity, periodic support, search space exploration techniques, and pruning strategies are discussed. The main types of algorithms are also presented such as periodic-frequent pattern growth, partial periodic pattern-growth, and periodic high-utility itemset mining algorithm. Challenges and research opportunities are reviewed.

The chapters that follow present state-of-the-art techniques for discovering periodic patterns in (1) transactional databases, (2) temporal databases, (3) quantitative temporal databases, and (4) big data. Then, the theory on concise representations of periodic patterns is presented, as well as hiding sensitive information using privacy-preserving data mining techniques.

The book concludes with several applications of periodic pattern mining, including applications in air pollution data analytics, accident data analytics, and traffic congestion analytics.

This book gathers selected papers presented at the International Conference on Machine Intelligence and Soft Computing (ICMISC 2021), organized by Koneru Lakshmaiah Education Foundation, Guntur, Andhra Pradesh, India during 22 – 24 September 2021. The topics covered in the book include the artificial neural networks and fuzzy logic, cloud computing, evolutionary algorithms and computation, machine learning, metaheuristics and swarm intelligence, neuro-fuzzy system, soft computing and decision support systems, soft computing applications in actuarial science, soft computing for database deadlock resolution, soft computing methods in engineering, and support vector machine.