Titlebook: Big Data Analytics and Knowledge Discovery; 24th International C Robert Wrembel,Johann Gamper,Ismail Khalil Conference proceedings 2022 The

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书目名称Big Data Analytics and Knowledge Discovery影响因子(影响力)




书目名称Big Data Analytics and Knowledge Discovery影响因子(影响力)学科排名




书目名称Big Data Analytics and Knowledge Discovery网络公开度




书目名称Big Data Analytics and Knowledge Discovery网络公开度学科排名




书目名称Big Data Analytics and Knowledge Discovery被引频次




书目名称Big Data Analytics and Knowledge Discovery被引频次学科排名




书目名称Big Data Analytics and Knowledge Discovery年度引用




书目名称Big Data Analytics and Knowledge Discovery年度引用学科排名




书目名称Big Data Analytics and Knowledge Discovery读者反馈




书目名称Big Data Analytics and Knowledge Discovery读者反馈学科排名

CLOUT

Forschungen aus Staat und Rechtation of QJO, thanks to suffix arrays initially introduced for string processing, enabling efficient algorithms for data compression, repeat finding, etc. Firstly, we show the flexibility of suffix arrays in coding analytical queries, capturing shareable subexpressions, and incorporating QJO. Second

Amorous

https://doi.org/10.1007/978-3-662-25528-5 processes as a generic data model to capture and consolidate process variants into a reference process model; (ii) a process warehouse model to perform typical online analytical processing operations on different variation parts thus providing support to decision-making through KPIs; The framework

Mendicant

https://doi.org/10.1007/978-3-7091-0597-9tance scores include a notion of redundancy awareness making them a tool to achieve redundancy-free feature selection. We show that the deriving features’ selection outperforms competing methods in lowering the redundancy rate while maximizing the information contained in the data. We also introduce

Virtues

Chaoyang Zhang,Jing Huang,Rupeng Buposition way and multi-output regression (MOR), respectively. To the best of our knowledge, such two algorithms are the first proposed embedded-type OSFS technique for multi-label streaming features so far. Our extensive experiments conducted on six benchmark data sets demonstrate that our two propo

GEON

Chaoyang Zhang,Jing Huang,Rupeng Bu set of relevant features with no protected features and with the least possible redundancy under prediction quality constraint. This constraint consists of a trade-off between fairness and prediction performance. Our experiments on well-known biased datasets from the literature demonstrated that ou

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Safeness: Suffix Arrays Driven Materialized View Selection Framework for Large-Scale Workloadsation of QJO, thanks to suffix arrays initially introduced for string processing, enabling efficient algorithms for data compression, repeat finding, etc. Firstly, we show the flexibility of suffix arrays in coding analytical queries, capturing shareable subexpressions, and incorporating QJO. Second

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浪荡子

Unsupervised Features Ranking via Coalitional Game Theory for Categorical Datatance scores include a notion of redundancy awareness making them a tool to achieve redundancy-free feature selection. We show that the deriving features’ selection outperforms competing methods in lowering the redundancy rate while maximizing the information contained in the data. We also introduce