Titlebook: Big Data Analytics and Knowledge Discovery; 22nd International C Min Song,Il-Yeol Song,Ismail Khalil Conference proceedings 2020 Springer N

miserly

書目名稱Big Data Analytics and Knowledge Discovery影響因子(影響力)




書目名稱Big Data Analytics and Knowledge Discovery影響因子(影響力)學(xué)科排名




書目名稱Big Data Analytics and Knowledge Discovery網(wǎng)絡(luò)公開度




書目名稱Big Data Analytics and Knowledge Discovery網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Big Data Analytics and Knowledge Discovery被引頻次




書目名稱Big Data Analytics and Knowledge Discovery被引頻次學(xué)科排名




書目名稱Big Data Analytics and Knowledge Discovery年度引用




書目名稱Big Data Analytics and Knowledge Discovery年度引用學(xué)科排名




書目名稱Big Data Analytics and Knowledge Discovery讀者反饋




書目名稱Big Data Analytics and Knowledge Discovery讀者反饋學(xué)科排名

CLAP

DHE,: Distributed Hybrid Evolution Engine for Performance Optimizations of Computationally Intensiveon top of the MapReduce open-source implementation in Apache Hadoop. Within DHE., we propose and implement two distributed hybrid evolution models, i.e., the MasterSlaveIslands and MicroMacroIslands models, alongside a real-world application that avoids the local optimum for clustering in an efficie

PANIC

SONDER: A Data-Driven Methodology for Designing Net-Zero Energy Public Buildingscollaboration between nZEB actors. In this paper, we share our vision for developing Energy Management Systems for nZEB as part of .. First, we propose a comprehensive methodology (SONDER), associated with a well-identified life cycle for developing data-driven solutions. Secondly, an instantiation

運(yùn)動(dòng)性

HANDLE - A Generic Metadata Model for Data LakesHANDLE’s feasibility through the application to an exemplary access-use-case and a prototypical implementation. A comparison with existent models yields that HANDLE can reflect the same information and provides additional capabilities needed for metadata management in data lakes.

多產(chǎn)子

adj憂郁的

High-Utility Interval-Based Sequences and persist over varying periods of time. An algorithm named . (.) is proposed and applied to real datasets. To achieve an efficient solution, HUIPMiner is augmented with a pruning strategy. Experimental results show that HUIPMiner is an effective solution to the problem of mining high utility inte

AVOID

debris

Mining Attribute Evolution Rules in Dynamic Attributed Graphsalues of multiple vertices may influence those of others with a high confidence. An efficient algorithm named AER-Miner is proposed to find these rules. Experiments on real data show AER-Miner is efficient and that AERs can provide interesting insights about dynamic attributed graphs.

送秋波

ELATE

https://doi.org/10.1007/978-1-4842-5623-7on top of the MapReduce open-source implementation in Apache Hadoop. Within DHE., we propose and implement two distributed hybrid evolution models, i.e., the MasterSlaveIslands and MicroMacroIslands models, alongside a real-world application that avoids the local optimum for clustering in an efficie