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. Datalog and Recursive Query Processing surveys for a general audience the Datalog language, recursive query processing, and optimization;
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, including roots in Datalog, extensions for networked environments, and the semantics of long-running queries over network state. The book focuses on;
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This research book presents key developments, directions, and challenges concerning advanced query processing for both traditional and non;
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uncertain data, and finally discuss the advanced query processing techniques for various probabilistic queries in uncertain databases. The book;
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The aim of query processing is to find information in one or more databases and deliver it to the user quickly and efficiently;
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Recently, much attention has been paid to image processing with multi-resolution and hierarchical structures such as pyramids and trees;
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initial submissions. Datalog 2.0 is a workshop for Datalog pioneers, implementors, and current practitioners; the contributions aim to bring every;
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uncertain data, and finally discuss the advanced query processing techniques for various probabilistic queries in uncertain databases. The book;
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, with larger indexes, more complex retrieval strategies and growing query volumes. Hence, there is a need for efficient query processing;
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The book covers the most crucial parts of real-time hyperspectral image processing: causality and real-time capability. Recently, two new;
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management; indexing and distributed systems; network embedding; trajectory and time series data processing; data mining; query processing and;
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; indexing and distributed systems; network embedding; trajectory and time series data processing; data mining; query processing and optimization;
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papers are grouped in topical sections on world wide web, recommendation, query processing and algorithm, natural language processing, machine;
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Multirate Signal processing can improve system performance and reduce costs in applications ranging from laboratory instruments, cable;
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. This book presents the state of the art in representation formalisms and query processing techniques for probabilistic data. It starts by;
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community and the Al community have studied various aspects of probabilistic relational data. Query Processing on Probabilistic Data: A Survey;
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selected from a total of 159 submissions. The topics covered are query processing and optimization, data semantics, XML and semi-structured data;
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Tackle the toughest set-based querying and query tuning problems-guided by an author team with in-depth, inside knowledge of T-SQL. Deepen;
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. This book presents the state of the art in representation formalisms and query processing techniques for probabilistic data. It starts by;
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event processing track, existential rules and datalog+/- track; legal rules and reasoning track; rule learning track; industry track.;
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and selected from 16 submissions. The scale and the heterogenous nature of web data poses many challenges, and turns basic tasks such as query;
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covers features that are often not well known, and sometimes not implemented in competing products. Chapters on query transformation and logical;
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raises new challenges in query semantics and processing, making conventional methods inapplicable. Furthermore, the interplay between ranking and;
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and selected from a total of 227 submissions. The topics covered in part 1 are social networks; query processing; nearest neighbor search;
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and selected from a total of 227 submissions. The topics covered in part 1 are social networks; query processing; nearest neighbor search;
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in order to preserve the sensitivity of some attribute values. Query processing is a fundamental problem in computer science, and is useful;
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