This book illustrates important ways in which new parallel hardware is being used to improve the speed and usefulness of a variety of information systems. It contains thirteen original papers that survey the latest trends in performance enhancing architectures for smart information systems. The machines featured in the text have been designed to support information systems ranging from relational databases to semantic networks and other artificial intelligence paradigms. In addition, many of the projects illustrated in the book contain generic architectural ideas that support higher-level requirements by using semantics-free hardware designs. The case studies describe add-on machines and performance-enhancing units that employ parallel hardware to speed up database operations. Other case studies show how high-performance computers support database and related software, even though some platforms were originally designed for scientific or numeric applications. The last three chapters give examples of machines that are deliberately designed to speed up a particular knowledge representation formalism or a particular AI problem solving paradigm. The information presented throughout this book will help all those engaged in the design or use of high-performance architectures for nonnumeric (i.e., symbolic) applications.
Emerging Trends in Database and Knowledge Based Machines
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Description
This book illustrates important ways in which new parallel hardware is being used to improve the speed and usefulness of a variety of information systems. It contains thirteen original papers that survey the latest trends in performance enhancing architectures for smart information systems. The machines featured in the text have been designed to support information systems ranging from relational databases to semantic networks and other artificial intelligence paradigms. In addition, many of the projects illustrated in the book contain generic architectural ideas that support higher-level requirements by using semantics-free hardware designs. The case studies describe add-on machines and performance-enhancing units that employ parallel hardware to speed up database operations. Other case studies show how high-performance computers support database and related software, even though some platforms were originally designed for scientific or numeric applications. The last three chapters give examples of machines that are deliberately designed to speed up a particular knowledge representation formalism or a particular AI problem solving paradigm. The information presented throughout this book will help all those engaged in the design or use of high-performance architectures for nonnumeric (i.e., symbolic) applications.
The three volume proceedings LNAI 11051 - 11053 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2018, held in...
The multi-volume set LNAI 12975 until 12979 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2021, which was held...
This two-volume set constitutes the refereed proceedings of the workshops which complemented the 21th Joint European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD,...
This volume contains the papers presented at the Fourth International Workshop on Database Machines. The papers cover a wide spectrum of topics including descrip tions of database machine...
This book constitutes the refereed conference proceedings of the 29th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2016, held in...
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