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Data Management and Query Processing in Semantic Web Databases

key issue for Semantic Web applications. In his book, Groppe details various aspects of high-performance Semantic Web data management and;

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Database Systems for Advanced Applications

management; indexing and distributed systems; network embedding; trajectory and time series data processing; data mining; query processing and;

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Database Systems for Advanced Applications

carefully selected from a total of 300 submissions. The papers are organized around the following topics: semantic web and knowledge management;

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Web-Age Information Management

systems; big data; spatial and temporal databases; information extraction; new hardware and miscellaneous; query processing and optimization;

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Advances in Databases and Information Systems

; subsequence matching and streaming data; OLAP; graph databases; spatial data management; parallel and distributed data processing; query optimization;

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RDF Database Systems

applications, data models, indexing and query processing solutions.Understand the Semantic Web, RDF, RDFS, SPARQL, and OWL within the context;

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Database and Expert Systems Applications

: temporal, spatial and high dimensional databases; semantic Web and ontologies; modeling, linked open data; NoSQLm NewSQL, data integration;

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Database and Expert Systems Applications

: temporal, spatial and high dimensional databases; semantic Web and ontologies; modeling, linked open data; NoSQLm NewSQL, data integration;

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Database and Expert Systems Applications

, and Network Analysis; Linked Data; Data Analysis; NoSQL, NewSQL; Multimedia Data; Personal Information Management; Semantic Web and Ontologies;

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Database and Expert Systems Applications

, and Network Analysis; Linked Data; Data Analysis; NoSQL, NewSQL; Multimedia Data; Personal Information Management; Semantic Web and Ontologies;

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Database Management Systems

the database features. Every DBMS should also enable transaction and query management, by using tools for data storage and retrieval, data;

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Principles of Database Query Processing for Advanced Applications

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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Model and Data Engineering

, concurrent systems, machine learning, swarm optimization, query processing, semantic web, graph databases, formal methods, model-driven engineering;

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Query Processing over Uncertain Databases

uncertain data, and finally discuss the advanced query processing techniques for various probabilistic queries in uncertain databases. The book;

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Probabilistic Databases

in probabilistic data management such as top-k query processing, sequential probabilistic databases, indexing and materialized views, and Monte Carlo;

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Probabilistic Databases

in probabilistic data management such as top-k query processing, sequential probabilistic databases, indexing and materialized views, and Monte Carlo;

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Web-Age Information Management

temporal databases, recommender systems, graph data management, information retrieval, privacy and trust, query processing and optimization, social;

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Web-Age Information Management

temporal databases, recommender systems, graph data management, information retrieval, privacy and trust, query processing and optimization, social;

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Database and Expert Systems Applications

cloud databases; information retrieval; Semantic Web and ontologies; information processing; temporal, spatial, and high dimensional databases;

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Database and Expert Systems Applications

cloud databases; information retrieval; Semantic Web and ontologies; information processing; temporal, spatial, and high dimensional databases;

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Web and Big Data

and data quality; graph data processing; data mining, privacy and semantic analysis; text and log data management; social networks; data;

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Web and Big Data

and data quality; graph data processing; data mining, privacy and semantic analysis; text and log data management; social networks; data;

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Database and Expert Systems Applications

Continuous Query Language; Text Processing and Semantic Search; Indexing and Concurrency Control Methods; Data Warehouse and Data Stream Warehouse;

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Database and Expert Systems Applications

Continuous Query Language; Text Processing and Semantic Search; Indexing and Concurrency Control Methods; Data Warehouse and Data Stream Warehouse;

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Database Systems for Advanced Applications

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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Query Processing over Uncertain Databases

uncertain data, and finally discuss the advanced query processing techniques for various probabilistic queries in uncertain databases. The book;

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Model and Data Engineering

, semantic web, graph databases, formal methods, model-driven engineering, blockchain, cyber physical systems, IoT applications, and smart systems;

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