In this edition, we focused on big data analytics methods and tools that have been specifically developed for the domain of cultural heritage, as well as on experiences from the adaptation and/or ...application of general-purpose solutions in the domain of cultural heritage. The aim was to gather solutions, but also to summarise the lessons learnt, methodologies, and good practices that researchers and practitioners can use as a basis for their own work in the domain.
Knowledge engineering and data mining are fundamental topics in the area of artificial intelligence and knowledge-based systems. This Special Issue covers the entire knowledge engineering pipeline: ...from data acquisition and data mining to knowledge extraction and exploitation. The reader will find topics including data mining methods, multidimensional data analysis, supervised and unsupervised learning methods, methods of knowledge-based management, language ontologies, ontology learning, and others.
This open access book constitutes revised selected papers from the International Workshops held at the Third International Conference on Process Mining, ICPM 2021, which took place in Eindhoven, The ...Netherlands, during October 31–November 4, 2021. The conference focuses on the area of process mining research and practice, including theory, algorithmic challenges, and applications. The co-located workshops provided a forum for novel research ideas. The 28 papers included in this volume were carefully reviewed and selected from 65 submissions. They stem from the following workshops: 2nd International Workshop on Event Data and Behavioral Analytics (EDBA) 2nd International Workshop on Leveraging Machine Learning in Process Mining (ML4PM) 2nd International Workshop on Streaming Analytics for Process Mining (SA4PM) 6th International Workshop on Process Querying, Manipulation, and Intelligence (PQMI) 4th International Workshop on Process-Oriented Data Science for Healthcare (PODS4H) 2nd International Workshop on Trust, Privacy, and Security in Process Analytics (TPSA) One survey paper on the results of the XES 2.0 Workshop is included.
"Doing language science" depends on collecting, collecting, transcribing, annotating, analysing, storing, and sharing linguistic research data. This volume offers a guide to linguistic data ...management, engaging with current trends toward the transformation of linguistics into a more data-driven and reproducible scientific endeavour. It offers both principles and methods, presenting the conceptual foundations of linguistic data management and a series of case studies, each of which demonstrates a concrete application of abstract principles in a current practice. In part 1, contributors bring together knowledge from information science, archiving, and data stewardship relevant to linguistic data management. Topics covered include implementation principles, archiving data, finding and using datasets, and the valuation of time and effort involved in data management. Part 2 presents snapshots of practices across various subfields, with each chapter presenting a unique data management project with generalisable guidance for researchers. The Open Handbook of Linguistic Data Management is an essential addition to the toolkit of every linguist, guiding researchers toward making their data FAIR: Findable, Accessible, Interoperable, and Reusable.
Artificial intelligence (AI) and data mining is the fastest growing field in computer science. AI and data mining algorithms and techniques are found to be useful in different areas like pattern ...recognition, automatic threat detection, automatic problem solving, visual recognition, fraud detection, detecting developmental delay in children, and many other applications. However, applying AI and data mining techniques or algorithms successfully in these areas needs a concerted effort, fostering integrative research between experts ranging from diverse disciplines from data science to Artificial Intelligence. Successful application of security frameworks to enable meaningful, cost effective, personalize security service is a primary aim of engineers and researchers today. However realizing this goal requires effective understanding, application and amalgamation of AI and Data Mining and several other computing technologies to deploy such system in an effective manner. This book provides state of the art approaches of artificial intelligence and data mining in these areas. It includes areas of detection, prediction, as well as future framework identification, development, building service systems and analytical aspects. In all these topics, applications of AI and data mining, such as artificial neural networks, fuzzy logic, genetic algorithm and hybrid mechanisms, are explained and explored. This book is aimed at the modeling and performance prediction of efficient security framework systems, bringing to light a new dimension in the theory and practice. This groundbreaking new volume presents these topics and trends, bridging the research gap on AI and data mining to enable wide-scale implementation. Whether for the veteran engineer or the student, this is a must-have for any library.
Temporal Data Mining Mitsa, Theophano
2010, 2010-03-10T00:00:00, 2010-03-10
eBook
Temporal data mining deals with the harvesting of useful information from temporal data. New initiatives in health care and business organizations have increased the importance of temporal ...information in data today.From basic data mining concepts to state-of-the-art advances, Temporal Data Mining covers the theory of this subject as well as its app
This book argues that the fourth industrial revolution, the process of accelerated automation of traditional manufacturing and industrial practices via digital technology, will serve to further ...marginalise Africa within the international community. In this book, the author argues that the looting of Africa that started with human capital and then natural resources, now continues unabated via data and digital resources looting. Developing on the notion of "Coloniality of Data", the fourth industrial revolutionis postulated as the final phase which will conclude Africa’s peregrination towards recolonisation. Global cartels, networks of coloniality, and tech multi-national corporations have turned Big Data into capital, which is left unguarded in Africa as the continent lacks the strong institutions necessary to regulate the mining of data. Written from a decolonial perspective, this book employs three analytical pillars of coloniality of power, knowledge and being. It concludes with an assessment of what could be done to help to turn the fourth industrial revolution from a curse into a resource. Highlighting the crippling continuation of asymmetrical global power relations, this book will be an important read for researchers of African studies, politics and international political economy.
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