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Titlebook: Big Data Analytics and Knowledge Discovery; 20th International C Carlos Ordonez,Ladjel Bellatreche Conference proceedings 2018 Springer Nat

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發(fā)表于 2025-3-21 18:17:30 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱(chēng)Big Data Analytics and Knowledge Discovery
期刊簡(jiǎn)稱(chēng)20th International C
影響因子2023Carlos Ordonez,Ladjel Bellatreche
視頻videohttp://file.papertrans.cn/186/185604/185604.mp4
學(xué)科分類(lèi)Lecture Notes in Computer Science
圖書(shū)封面Titlebook: Big Data Analytics and Knowledge Discovery; 20th International C Carlos Ordonez,Ladjel Bellatreche Conference proceedings 2018 Springer Nat
影響因子This book constitutes the refereed proceedings of the 20th International Conference on Big Data Analytics and Knowledge Discovery, DaWaK 2018, held in Regensburg, Germany, in September 2018..The 13 revised full papers and 17 short papers presented were carefully reviewed and selected from 76 submissions. The papers are organized in the following topical sections: Graph analytics; case studies; classification and clustering; pre-processing; sequences; cloud and database systems; and data mining..
Pindex Conference proceedings 2018
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978-3-319-98538-1Springer Nature Switzerland AG 2018
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In-Cell NMR in Mammalian Cells: Part 2This paper focuses on the emerging field of graph warehousing. Graphs are widespread structures that yield a great expressive power. They are used for modeling highly complex and interconnected domains, and efficiently solving emerging big data application. This paper presents the current status and
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Intrinsically Disordered Protein Analysis datasets, there is a great potential for knowledge discovery. Since the processing pipeline contains several important steps, like data preparation, transformation, knowledge discovery, a holistic approach is required in order to avoid costly ETL operations across different heterogeneous systems. I
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Matthew D. Smith,Masoud Jelokhani-Niarakiridge suffers damage. We consider the detection of such anomalous responses, using data from both traffic-surveillance cameras and strain sensors. The camera data are utilized to treat each vehicle’s identified properties as explanatory variables in the response model. The video and strain data are
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