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This book contains proceedings of the International Conference on Advances in Computing, Control and Communication Technology (IAC3T) organized by Centre for Computer Education, Institute of Professional Studies, University of Allahabad during March 25-27, 2016 at Allahabad. A total of 138 full papers were submitted to the conference, out of which about 40 papers were accepted and finally 35 papers were presented during the conference. This book contains these papers. The conference was a major multidisciplinary conference organized with the objective to expose the participants to the emerging trends in the area of computing, control and communication technology. The conference intended to serve as a major international forum for the exchange of ideas and to provide an interactive platform to the students (budding engineers), engineers, researchers and academicians to exchange their innovative ideas and experiences in the area of advancements in computing, control and communication technology.
The Mexican International Conference on Artificial Intelligence (MICAI), a yearly international conference series organized by the Mexican Society for Artificial Intel- gence (SMIA), is a major international AI forum and the main event in the academic life of the country’s growing AI community. In 2008 Mexico celebrates the 50th an- versary of development of computer science in the country: in 1958 the first computer was installed at the National Autonomous University of Mexico (UNAM). Nowadays, computer science is the country’s fastest growing research area. The proceedings of the previous MICAI events were published by Springer in its Lecture Notes in Artificial Intelligence (LNAI) ser...
This publication covers papers presented at AIED2009, part of an ongoing series of biennial international conferences for top quality research in intelligent systems and cognitive science for educational computing applications. The conference provides opportunities for the cross-fertilization of techniques from many fields that make up this interdisciplinary research area, including: artificial intelligence, computer science, cognitive and learning sciences, education, educational technology, psychology, philosophy, sociology, anthropology, linguistics, and the many domain-specific areas for which AIED systems have been designed and evaluated. AIED2009 focuses on the theme ""Building learnin...
Modern education has increased its reach through ICT tools and techniques. To manage educational data with the help of modern artificial intelligence, data and web mining techniques on dedicated cloud or grid platforms for educational institutes can be used. By utilizing data science techniques to manage educational data, the safekeeping, delivery, and use of knowledge can be increased for better quality education. Utilizing Educational Data Mining Techniques for Improved Learning: Emerging Research and Opportunities is a critical scholarly resource that explores data mining and management techniques that promote the improvement and optimization of educational data systems. The book intends to provide new models, platforms, tools, and protocols in data science for educational data analysis and introduces innovative hybrid system models dedicated to data science. Including topics such as automatic assessment, educational analytics, and machine learning, this book is essential for IT specialists, data analysts, computer engineers, education professionals, administrators, policymakers, researchers, academicians, and technology experts.
This book constitutes the refereed proceedings of the 6th Mexican International Conference on Artificial Intelligence, MICAI 2007, held in Aguascalientes, Mexico, in November 2007. The 116 revised full papers presented were carefully reviewed and selected from numerous submissions for inclusion in the book. The papers are organized in sections on topics that include computational intelligence, neural networks, knowledge representation and reasoning, agents and multiagent systems.
This book describes theoretical elements, practical approaches, and specialized tools that systematically organize, characterize, and analyze big data gathered from educational affairs and settings. Moreover, the book shows several inference criteria to leverage and produce descriptive, explanatory, and predictive closures to study and understand education phenomena at in classroom and online environments. This is why diverse researchers and scholars contribute with valuable chapters to ground with well-–sounded theoretical and methodological constructs in the novel field of Educational Data Science (EDS), which examines academic big data repositories, as well as to introduces systematic r...
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