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Titlebook: Beyond Databases, Architectures and Structures. Advanced Technologies for Data Mining and Knowledge ; 12th International C Stanisław Koziel

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发表于 2025-3-21 18:16:35 | 显示全部楼层 |阅读模式
期刊全称Beyond Databases, Architectures and Structures. Advanced Technologies for Data Mining and Knowledge
期刊简称12th International C
影响因子2023Stanisław Kozielski,Dariusz Mrozek,Daniel Kostrzew
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发行地址Includes supplementary material:
学科分类Communications in Computer and Information Science
图书封面Titlebook: Beyond Databases, Architectures and Structures. Advanced Technologies for Data Mining and Knowledge ; 12th International C Stanisław Koziel
影响因子.This book constitutes the refereed proceedings of the 12th International Conference entitled Beyond Databases, Architectures and Structures, BDAS 2016, held in Ustroń, Poland, in May/June 2016...It consists of 57 carefully reviewed papers selected from 152 submissions. The papers are organized in topical sections, namely artificial intelligence, data mining and knowledge discovery; architectures, structures and algorithms for efficient data processing; data warehousing and OLAP; natural language processing, ontologies and semantic Web; bioinformatics and biomedical data analysis; data processing tools; novel applications of database systems..
Pindex Conference proceedings 2016
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Luc Lecavalier,Anne V. Snow,Megan Norrisy to measure the level of predictability of following procedure. The clustering approach used is essentially a way of personalizing patients according to their properties. The approach used in this work is entirely novel and was designed specifically to address the twofold problem of first being abl
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Beyond Databases, Architectures and Structures. Advanced Technologies for Data Mining and Knowledge 12th International C
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Stanisław Kozielski,Dariusz Mrozek,Daniel KostrzewIncludes supplementary material:
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Communications in Computer and Information Sciencehttp://image.papertrans.cn/b/image/185159.jpg
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Autism and Child Psychopathology Series scales up and out for large data to enable people to explore visually their data interactively in real-time as a means to understanding it. The five V’s of big data—., ., ., ., and .—each highlights the challenges of this endeavor..We present these challenges and a system, ., that we are developing
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Luc Lecavalier,Anne V. Snow,Megan Norrisive, data management based on parallel and cloud (e.g. MapReduce) systems are overviewed, and compared by relying on meeting software requirements (e.g. data independence, software reuse), high performance, scalability, elasticity, and data availability. With respect to proposed cloud systems, we di
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