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This book constitutes the refereed proceedings of the Third International Conference on Data Mining and Big Data, DMBD 2018, held in Shanghai, China, in June 2018. The 74 papers presented in this volume were carefully reviewed and selected from 126 submissions. They are organized in topical sections named: database, data preprocessing, matrix factorization, data analysis, visualization, visibility analysis, clustering, prediction, classification, pattern discovery, text mining and knowledge management, recommendation system in social media, deep learning, big data, Industry 4.0, practical applications
This book contains the refereed proceedings of the 13th International Conference on Knowledge Management in Organizations, KMO 2018, held in Žilina, Slovakia, in August 2018. The theme of the conference was "Emerging Research for Knowledge Management in Organizations." The 59 papers accepted for KMO 2018 were selected from 141 submissions and are organized in topical sections on: Knowledge management models and analysis; knowledge sharing; knowledge transfer and learning; knowledge and service innovation; knowledge creation; knowledge and organization; information systems and information science; knowledge and technology management; data mining and intelligent science; business and customer relationship management; big data and IoT; and new trends in IT.
The proceedings from the eighth KMO conference represent the findings of this international meeting which brought together researchers and developers from industry and the academic world to report on the latest scientific and technical advances on knowledge management in organizations. This conference provided an international forum for authors to present and discuss research focused on the role of knowledge management for innovative services in industries, to shed light on recent advances in social and big data computing for KM as well as to identify future directions for researching the role of knowledge management in service innovation and how cloud computing can be used to address many of the issues currently facing KM in academia and industrial sectors.
This book provides a forum for experts to present their latest research in disruptive technologies, promoting knowledge transfer. Due to the important advances in technologies such as artificial intelligence, big data, the Internet of things, or bioinformatics produced in recent years, it is necessary to conduct a thorough review of current ethical patterns. One of the research fields that is in full expansion and with a broad future is technology ethics or tech ethics. Just a few years ago, this type of research was a small part, and they did not have too many technology researchers involved. At present, due to the explosion of new applications of artificial intelligence, their problems and...
Users increasingly demand more from their software than ever beforemore features, fewer errors, faster runtimes. To deliver the best quality products possible, software engineers are constantly in the process of employing novel tools in developing the latest software applications. Progressions and Innovations in Model-Driven Software Engineering investigates the most recent and relevant research on model-driven engineering. Within its pages, researchers and professionals in the field of software development, as well as academics and students of computer science, will find an up-to-date discussion of scientific literature on the topic, identifying opportunities and advantages, and complexities and challenges, inherent in the future of software engineering.
This book is composed by the papers accepted for presentation and discussion at The 2019 International Conference on Information Technology & Systems (ICITS'20), held at the Universidad Distrital Francisco José de Caldas, in Bogotá, Colombia, on 5th to 7th February 2020. ICIST is a global forum for researchers and practitioners to present and discuss recent findings and innovations, current trends, professional experiences and challenges of modern information technology and systems research, together with their technological development and applications. The main topics covered are: information and knowledge management; organizational models and information systems; software and systems modelling; software systems, architectures, applications and tools; multimedia systems and applications; computer networks, mobility and pervasive systems; intelligent and decision support systems; big data analytics and applications; human–computer interaction; ethics, computers & security; health informatics; information technologies in education.
This book constitutes the refereed proceedings of the 7th International Workshop on Learning Technology for Education Challenges, LTEC 2018, held in Žilina, Slovakia, in August 2018. The 25 revised full papers presented were carefully reviewed and selected from 54 submissions. The papers are organized in the following topical sections: Gamification and learning; learning and knowledge transfer; learning technologies applications; virtual learning environments; and mobile learning and MOOCs. LTEC 2018 examines how these technologies and pedagogical advances can be used to change the way teachers teach and students learn, while giving special emphasis to the pedagogically effective ways we can harness these new technologies in education.
Professionals in the interdisciplinary field of computer science focus on the design, operation, and maintenance of computational systems and software. Methodologies and tools of engineering are utilized alongside the technological advancements of computer applications to develop efficient and precise databases of information. The Handbook of Research on Innovations in Systems and Software Engineering combines relevant research from all facets of computer programming to provide a comprehensive look at the challenges and changes in the field. With information spanning topics such as design models, cloud computing, and security, this handbook is an essential reference source for academicians, researchers, practitioners, and students interested in the development and design of improved and effective technologies.
This edited volume on machine learning and big data analytics (Proceedings of ICMLBDA 2022) is intended to be used as a reference book for researchers and professionals to share their research and reports of new technologies and applications in Machine Learning and Big Data Analytics like biometric Recognition Systems, medical diagnosis, industries, telecommunications, AI Petri Nets Model-Based Diagnosis, gaming, stock trading, Intelligent Aerospace Systems, robot control, law, remote sensing and scientific discovery agents and multiagent systems; and natural language and Web intelligence. The intent of this book is to provide awareness of algorithms used for machine learning and big data in the advanced Scientific Technologies, provide a correlation of multidisciplinary areas and become a point of great interest for Data Scientists, systems architects, developers, new researchers and graduate level students. This volume provides cutting-edge research from around the globe on this field. Current status, trends, future directions, opportunities, etc. are discussed, making it friendly for beginners and young researchers.
La apertura de los datos produce beneficios para todos los que participan de ella: los ciudadanos, las empresas y la propia administración. El reto está en procesar cantidades enormes de datos y convertirlos en decisiones inteligentes y oportunas, por eso se hace necesario aprovechar esta importante oportunidad de crear valor. Este libro presenta un panorama de las diferentes iniciativas a nivel mundial y regional y los desafíos asociados con su construcción.