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	Proceedings of the VLDB Endowment         Options: Date Reviewed Title Author Publisher Published Date Descending Order Ascending Order     1-8 of 8 reviews Date Reviewed     Scalable and efficient data analytics and mining with Lemonade dos Santos W., Avelar G., Ribeiro M., Guedes D., Meira Jr. W. Proceedings of the VLDB Endowment 11(12): 2070-2073, 2018.  Type: Article It is unreasonable to assume that data analysis experts are adept at computer programming. However, many tools that a data analyst may want to use require significant programming skills. Moreover, with the amount of information availab... May 21 2019   Husky: towards a more efficient and expressive distributed computing framework Yang F., Li J., Cheng J. Proceedings of the VLDB Endowment 9(5): 420-431, 2016.  Type: Article Husky is a continuity point on the scientific approach to massive data computing, an approach that is still at the peak of hype. This approach certainly would be the origin of further investigation to provide a more effective framework... Feb 7 2017   Worker skill estimation in team-based tasks Rahman H., Thirumuruganathan S., Roy S., Amer-Yahia S., Das G. Proceedings of the VLDB Endowment 8(11): 1142-1153, 2015.  Type: Article Estimating the skills of individuals is acknowledged to be an important open problem with vast applications to optimal team formation. One difficulty with skill estimation is that the skills in question are generally considered to be &... Sep 6 2016   Mega-KV: a case for GPUs to maximize the throughput of in-memory key-value stores Zhang K., Wang K., Yuan Y., Guo L., Lee R., Zhang X. Proceedings of the VLDB Endowment 8(11): 1226-1237, 2015.  Type: Article When a central processing unit (CPU) is augmented by a graphics processing unit (GPU), compute-intensive functions can be offloaded to the GPU. While a CPU typically contains a few cores, current generation GPUs contain over 2,000 core... Aug 11 2016   Constructing an interactive natural language interface for relational databases Li F., Bonifati A. Proceedings of the VLDB Endowment 8(1): 73-84, 2014.  Type: Article The Internet of Things is democratizing computer usage, with computers metamorphosing into communication devices making their way from offices to inside people’s homes, cars, factories, and so on. Data access on these compute... Aug 10 2016   Clash of the titans: MapReduce vs. Spark for large scale data analytics Shi J., Qiu Y., Minhas U., Jiao L., Wang C., Reinwald B., Özcan F. Proceedings of the VLDB Endowment 8(13): 2110-2121, 2015.  Type: Article Analyzing big data has never been more important in computer science, and the platforms of choice have been either MapReduce or Spark. By using selected workloads that characterize the majority of batch and iterative analytic operation... Jun 29 2016   MillWheel: fault-tolerant stream processing at Internet scale Akidau T., Balikov A., Bekiroğlu K., Chernyak S., Haberman J., Lax R., McVeety S., Mills D., Nordstrom P., Whittle S. Proceedings of the VLDB Endowment 6(11): 1033-1044, 2013.  Type: Article In this paper, the authors introduce MillWheel, a framework for processing real-time streamed data that is used at Google. It is based on the paradigm of streaming computing, in which users specify a computation graph and provide code ... Apr 11 2014   A distributed graph engine for web scale RDF data Zeng K., Yang J., Wang H., Shao B., Wang Z. Proceedings of the VLDB Endowment 6(4): 265-276, 2013.  Type: Article Designing a scalable resource description framework (RDF) data graph engine is a difficult task. In this paper, the authors present Trinity.RDF, a distributed memory-based graph engine for web-scale RDF data. This approach stores RDF d... Mar 26 2014       Display 510152550100 per column
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