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This open access book is part of the LAMBDA Project (Learning, Applying, Multiplying Big Data Analytics), funded by the European Union, GA No. 809965. Data Analytics involves applying algorithmic processes to derive insights. Nowadays it is used in many industries to allow organizations and companies to make better decisions as well as to verify or disprove existing theories or models. The term data analytics is often used interchangeably with intelligence, statistics, reasoning, data mining, knowledge discovery, and others. The goal of this book is to introduce some of the definitions, methods, tools, frameworks, and solutions for big data processing, starting from the process of information extraction and knowledge representation, via knowledge processing and analytics to visualization, sense-making, and practical applications. Each chapter in this book addresses some pertinent aspect of the data processing chain, with a specific focus on understanding Enterprise Knowledge Graphs, Semantic Big Data Architectures, and Smart Data Analytics solutions. This book is addressed to graduate students from technical disciplines, to professional audiences following continuous education short courses, and to researchers from diverse areas following self-study courses. Basic skills in computer science, mathematics, and statistics are required.
Information systems are the backbone of many of today's computerized applications. Distributed databases and the infrastructure needed to support them have been well studied. However, this book is the first to address distributed database interoperability by examining the successes and failures, various approaches, infrastructures, and trends of the field. A gap exists in the way that these systems have been investigated by real practitioners. This gap is more pronounced than usual, partly because of the way businesses operate, the systems they have, and the difficulties created by systems' autonomy and heterogeneity. Telecommunications firms, for example, must deal with an increased demand for automation while at the same time continuing to function at their current level. While academics are focusing on investigating differences between distributed databases, federated databases, heterogeneous databases, and, more generally, among loosely connected and tightly coupled systems, those who have to deal with real problems right away know that the only relevant research is the one that will ensure that their system works to produce reasonably correct results. Interconnecting Heterogeneous Information Systems covers the underlying principles and infrastructures needed to realize truly global information systems. The book discusses technologies related to middleware, the Web, workflows, transactions, and data warehousing. It also overviews architectures with a discussion of critical issues. The book gives an overview of systems that can be viewed as learning platforms. While these systems do not translate to successful commercial realities, they push the envelope in terms of research. Successful commercial systems have benefited from the experiments conducted in these prototypes. The book includes two case studies based on the authors' own work. Interconnecting Heterogeneous Information Systems is suitable as a textbook for a graduate-level course on Interconnecting Heterogeneous Information Systems, as well as a secondary text for a graduate-level course on database or information systems, and as a reference for researchers and practitioners in industry.
This is the silver anniversary of one of the longest running database conferences. VLDB is among the best established forums for discussion in the international database community and is organized every year by the VLDB Endowment.
Held in Vienna, Austria, April 1993, the workshop heard work-in-progress, industrial, and position papers, which are presented along with panel discussions. Among the topics: lean languages and models, interdatabase consistency and constraints, schematic issues, query processing and optimization, tr
This proceedings volume contains 52 technical research papers on multidatabases, distributed DB, multimedia DB, object-oriented DB, real-time DB, temporal DB, deductive DB, and intelligent user interface. Some industrial papers are also included.
The field of agent and multi-agent systems is concerned with the development and evaluation of sophisticated, AI-based, problem solving and control architectures for both single and multi-agent systems. This book presents the proceedings of the 7th KES Conference on Agent and Multi-agent Systems – Technologies and Applications (KES-AMSTA 2013), held in Hue City, Vietnam, in May 2013. The KES-AMSTA 2013 conference provides an internationally respected forum for scientific research in the technologies and applications of agent and multi-agent systems. In all, 44 papers were selected for oral presentation and publication in this volume. Special attention is paid to the feature topics of intelligent technologies and applications in the area of e-health, social networking, self-organizing systems, economics and trust management. Other topics covered include: agent oriented software engineering; beliefs engineering; desires and intentions representation; agent cooperation, coordination, negotiation, organization and communication; distributed problem-solving; specification of agent communication languages; formalization of ontologies; and conversational agents. The book highlights new trends and challenges in agent and multi-agent research, and will be of interest to the research community working in the fields of artificial intelligence, collective computational intelligence, robotics, dialogue systems and, in particular, agent and multi-agent systems, technologies and applications.