Efficient Optimization And Processing Of Queries Over Text Rich Graph Structured Data
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Efficient Optimization And Processing Of Queries Over Text Rich Graph Structured Data
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Author : Günter Ladwig
language : en
Publisher: KIT Scientific Publishing
Release Date : 2014-05-13
Efficient Optimization And Processing Of Queries Over Text Rich Graph Structured Data written by Günter Ladwig and has been published by KIT Scientific Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-05-13 with Electronic computers. Computer science categories.
Many databases today capture both, structured and unstructured data. Making use of such hybrid data has become an important topic in research and industry. The efficient evaluation of hybrid data queries is the main topic of this thesis. Novel techniques are proposed that improve the whole processing pipeline, from indexes and query optimization to run-time processing. The contributions are evaluated in extensive experiments showing that the proposed techniques improve upon the state of the art.
Efficient Optimization And Processing Of Queries Over Text Rich Graph Structured Data
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Author : Günter Ladwig
language : en
Publisher:
Release Date : 2013
Efficient Optimization And Processing Of Queries Over Text Rich Graph Structured Data written by Günter Ladwig and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with categories.
Many databases today capture both, structured and unstructured data. Making use of such hybrid data has become an important topic in research and industry. The efficient evaluation of hybrid data queries is the main topic of this thesis. Novel techniques are proposed that improve the whole processing pipeline, from indexes and query optimization to run-time processing. The contributions are evaluated in extensive experiments showing that the proposed techniques improve upon the state of the art.
Ranking For Web Data Search Using On The Fly Data Integration
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Author : Herzig, Daniel Markus
language : en
Publisher: KIT Scientific Publishing
Release Date : 2014-01-21
Ranking For Web Data Search Using On The Fly Data Integration written by Herzig, Daniel Markus and has been published by KIT Scientific Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-01-21 with categories.
Query Processing Over Graph Structured Data On The Web
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Author : M. Acosta Deibe
language : en
Publisher: IOS Press
Release Date : 2018-10-12
Query Processing Over Graph Structured Data On The Web written by M. Acosta Deibe and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-12 with Computers categories.
In the last years, Linked Data initiatives have encouraged the publication of large graph-structured datasets using the Resource Description Framework (RDF). Due to the constant growth of RDF data on the web, more flexible data management infrastructures must be able to efficiently and effectively exploit the vast amount of knowledge accessible on the web. This book presents flexible query processing strategies over RDF graphs on the web using the SPARQL query language. In this work, we show how query engines can change plans on-the-fly with adaptive techniques to cope with unpredictable conditions and to reduce execution time. Furthermore, this work investigates the application of crowdsourcing in query processing, where engines are able to contact humans to enhance the quality of query answers. The theoretical and empirical results presented in this book indicate that flexible techniques allow for querying RDF data sources efficiently and effectively.
Querying Graphs
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Author : Angela Bonifati
language : en
Publisher: Morgan & Claypool Publishers
Release Date : 2018-10-01
Querying Graphs written by Angela Bonifati and has been published by Morgan & Claypool Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-01 with Computers categories.
Graph data modeling and querying arises in many practical application domains such as social and biological networks where the primary focus is on concepts and their relationships and the rich patterns in these complex webs of interconnectivity. In this book, we present a concise unified view on the basic challenges which arise over the complete life cycle of formulating and processing queries on graph databases. To that purpose, we present all major concepts relevant to this life cycle, formulated in terms of a common and unifying ground: the property graph data model—the pre-dominant data model adopted by modern graph database systems. We aim especially to give a coherent and in-depth perspective on current graph querying and an outlook for future developments. Our presentation is self-contained, covering the relevant topics from: graph data models, graph query languages and graph query specification, graph constraints, and graph query processing. We conclude by indicating major open research challenges towards the next generation of graph data management systems.
Query Processing Over Graph Structured Data On The Web
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Author : Maribel Acosta Deibe
language : en
Publisher:
Release Date : 2018
Query Processing Over Graph Structured Data On The Web written by Maribel Acosta Deibe and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with categories.
Graph Algorithms For Data Science
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Author : Tomaž Bratanic
language : en
Publisher: Simon and Schuster
Release Date : 2024-03-12
Graph Algorithms For Data Science written by Tomaž Bratanic and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-12 with Computers categories.
Practical methods for analyzing your data with graphs, revealing hidden connections and new insights. Graphs are the natural way to represent and understand connected data. This book explores the most important algorithms and techniques for graphs in data science, with concrete advice on implementation and deployment. You don’t need any graph experience to start benefiting from this insightful guide. These powerful graph algorithms are explained in clear, jargon-free text and illustrations that makes them easy to apply to your own projects. In Graph Algorithms for Data Science you will learn: Labeled-property graph modeling Constructing a graph from structured data such as CSV or SQL NLP techniques to construct a graph from unstructured data Cypher query language syntax to manipulate data and extract insights Social network analysis algorithms like PageRank and community detection How to translate graph structure to a ML model input with node embedding models Using graph features in node classification and link prediction workflows Graph Algorithms for Data Science is a hands-on guide to working with graph-based data in applications like machine learning, fraud detection, and business data analysis. It’s filled with fascinating and fun projects, demonstrating the ins-and-outs of graphs. You’ll gain practical skills by analyzing Twitter, building graphs with NLP techniques, and much more. Foreword by Michael Hunger. About the technology A graph, put simply, is a network of connected data. Graphs are an efficient way to identify and explore the significant relationships naturally occurring within a dataset. This book presents the most important algorithms for graph data science with examples from machine learning, business applications, natural language processing, and more. About the book Graph Algorithms for Data Science shows you how to construct and analyze graphs from structured and unstructured data. In it, you’ll learn to apply graph algorithms like PageRank, community detection/clustering, and knowledge graph models by putting each new algorithm to work in a hands-on data project. This cutting-edge book also demonstrates how you can create graphs that optimize input for AI models using node embedding. What's inside Creating knowledge graphs Node classification and link prediction workflows NLP techniques for graph construction About the reader For data scientists who know machine learning basics. Examples use the Cypher query language, which is explained in the book. About the author Tomaž Bratanic works at the intersection of graphs and machine learning. Arturo Geigel was the technical editor for this book. Table of Contents PART 1 INTRODUCTION TO GRAPHS 1 Graphs and network science: An introduction 2 Representing network structure: Designing your first graph model PART 2 SOCIAL NETWORK ANALYSIS 3 Your first steps with Cypher query language 4 Exploratory graph analysis 5 Introduction to social network analysis 6 Projecting monopartite networks 7 Inferring co-occurrence networks based on bipartite networks 8 Constructing a nearest neighbor similarity network PART 3 GRAPH MACHINE LEARNING 9 Node embeddings and classification 10 Link prediction 11 Knowledge graph completion 12 Constructing a graph using natural language processing technique
Main Memory Management On Relational Database Systems
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Author : Pedro Mejia Alvarez
language : en
Publisher: Springer Nature
Release Date : 2022-09-13
Main Memory Management On Relational Database Systems written by Pedro Mejia Alvarez and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-09-13 with Computers categories.
This book provides basic knowledge about main memory management in relational databases as it is needed to support large-scale applications processed completely in memory. In business operations, real-time predictability and high speed is a must. Hence every opportunity must be exploited to improve performance, including reducing dependency on the hard disk, adding more memory to make more data resident in the memory, and even deploying an in-memory system where all data can be kept in memory. The book provides one chapter for each of the main related topics, i.e. the memory system, memory management, virtual memory, and databases and their memory systems, and it is complemented by a short survey of six commercial systems: TimesTen, MySQL, VoltDB, Hekaton, HyPer/ScyPer, and SAP HANA.
Multimedia Modeling
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Author : Björn Þór Jónsson
language : en
Publisher: Springer Nature
Release Date : 2022-03-14
Multimedia Modeling written by Björn Þór Jónsson and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-14 with Computers categories.
The two-volume set LNCS 13141 and LNCS 13142 constitutes the proceedings of the 28th International Conference on MultiMedia Modeling, MMM 2022, which took place in Phu Quoc, Vietnam, during June 6–10, 2022. The 107 papers presented in these proceedings were carefully reviewed and selected from a total of 212 submissions. They focus on topics related to multimedia content analysis; multimedia signal processing and communications; and multimedia applications and services.
Dissertation Abstracts International
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Author :
language : en
Publisher:
Release Date : 2009
Dissertation Abstracts International written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with Dissertations, Academic categories.