Ict Innovations 2019 Big Data Processing And Mining

This book constitutes the refereed proceedings of the 11th International ICT Innovations Conference, ICT Innovations 2019, held in Ohrid, Macedonia, in October 2019. The 18 full papers presented were carefully reviewed and selected from 75 submissions. They cover the following topics: sensor applications and deployments, embedded and cyber-physical systems, robotics, network architectures, cloud computing, software infrastructure, software creation and management, models of computation, computational complexity and cryptography, design and analysis of algorithms, mathematical optimization, probability and statistics, data management systems, data mining, human computer interaction (HCI), artificial intelligence, machine learning, life and medical sciences, health care information systems, bioinformatics.

This book constitutes the refereed proceedings of the 11th International ICT Innovations Conference, ICT Innovations 2019, held in Ohrid, Macedonia, in October 2019. The 18 full papers presented were carefully reviewed and selected from 75 submissions. They cover the following topics: sensor applications and deployments, embedded and cyber-physical systems, robotics, network architectures, cloud computing, software infrastructure, software creation and management, models of computation, computational complexity and cryptography, design and analysis of algorithms, mathematical optimization, probability and statistics, data management systems, data mining, human computer interaction (HCI), artificial intelligence, machine learning, life and medical sciences, health care information systems, bioinformatics. --

This book addresses the usefulness of knowledge discovery through data mining. With this aim, contributors from different fields propose concrete problems and applications showing how data mining and discovering embedded knowledge from raw data can be beneficial to social organizations, domestic spheres, and ICT markets. Data mining or knowledge discovery in databases (KDD) has received increasing interest due to its focus on transforming large amounts of data into novel, valid, useful, and structured knowledge by detecting concealed patterns and relationships. The concept of knowledge is broad and speculative and has promoted epistemological debates in western philosophies. The intensified interest in knowledge management and data mining stems from the difficulty in identifying computational models able to approximate human behaviors and abilities in resolving organizational, social, and physical problems. Current ICT interfaces are not yet adequately advanced to support and simulate the abilities of physicians, teachers, assistants or housekeepers in domestic spheres. And unlike in industrial contexts where abilities are routinely applied, the domestic world is continuously changing and unpredictable. There are challenging questions in this field: Can knowledge locked in conventions, rules of conduct, common sense, ethics, emotions, laws, cultures, and experiences be mined from data? Is it acceptable for automatic systems displaying emotional behaviors to govern complex interactions based solely on the mining of large volumes of data? Discussing multidisciplinary themes, the book proposes computational models able to approximate, to a certain degree, human behaviors and abilities in resolving organizational, social, and physical problems. The innovations presented are of primary importance for: a. The academic research community b. The ICT market c. Ph.D. students and early stage researchers d. Schools, hospitals, rehabilitation and assisted-living centers e. Representatives from multimedia industries and standardization bodies

This book presents the latest findings in the areas of data management and smart computing, big data management, artificial intelligence and data analytics, along with advances in network technologies. It addresses state-of-the-art topics and discusses challenges and solutions for future development. Gathering original, unpublished contributions by scientists from around the globe, the book is mainly intended for a professional audience of researchers and practitioners in academia and industry.

This book gathers selected high-quality research papers presented at the Seventh International Congress on Information and Communication Technology, held at Brunel University, London, on February 21–24, 2022. It discusses emerging topics pertaining to information and communication technology (ICT) for managerial applications, e-governance, e-agriculture, e-education and computing technologies, the Internet of Things (IoT) and e-mining. Written by respected experts and researchers working on ICT, the book offers a valuable asset for young researchers involved in advanced studies. The work is presented in four volumes.

This book constitutes the refereed proceedings of the 4th International Conference on Data Mining and Big Data, DMBD 2019, held in Chiang Mai, Thailand, in July 2019. The 26 full papers and 8 short papers presented in this volume were carefully reviewed and selected from 79 submissions. They are organized in topical sections named: data analysis; prediction; clustering; classification; mining pattern; mining tasks.

This book presents emerging concepts in data mining, big data analysis, communication, and networking technologies, and discusses the state-of-the-art in data engineering practices to tackle massive data distributions in smart networked environments. It also provides insights into potential data distribution challenges in ubiquitous data-driven networks, highlighting research on the theoretical and systematic framework for analyzing, testing and designing intelligent data analysis models for evolving communication frameworks. Further, the book showcases the latest developments in wireless sensor networks, cloud computing, mobile network, autonomous systems, cryptography, automation, and other communication and networking technologies. In addition, it addresses data security, privacy and trust, wireless networks, data classification, data prediction, performance analysis, data validation and verification models, machine learning, sentiment analysis, and various data analysis techniques.

This book features the proceedings of The EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing (BDCC 2020), which took place 18 – 19 December 2020. The papers feature detail on cognitive computing and its self-learning systems that use data mining, pattern recognition and natural language processing (NLP) to mirror the way the human brain works. This international conference focuses on technologies from knowledge representation techniques and natural language processing algorithms to dynamic learning approaches. Topics covered include Data Science for Cognitive Analysis, Real-Time Ubiquitous Data Science, Platform for Privacy Preserving Data Science, and Internet-Based Cognitive Platform.