concise
发表于 2025-3-27 00:00:48
ribes the frameworks relevant to data science, and their appThis illuminating text/reference surveys the state of the art in data science, and provides practical guidance on big data analytics. Expert perspectives are provided by authoritative researchers and practitioners from around the world, dis
Crayon
发表于 2025-3-27 01:56:45
Compounds of Arsenic, Antimony, and Bismuthfuzzy set. This approximation allows to divide the whole graph into multiple subgraphs that can be processed independently. Then, for each subgraph, a MapReduce-based greedy algorithm can be designed to identify the minimum-sized influential vertices for the whole graph.
过剩
发表于 2025-3-27 08:03:48
https://doi.org/10.1007/978-3-642-50290-3ility. This chapter provides the introductory material about the various Hadoop ecosystem tools and describes their usage with data analytics. Each tool has its own significance in its functions in data analytics environment.
钢盔
发表于 2025-3-27 09:40:09
http://reply.papertrans.cn/27/2631/263086/263086_34.png
丑恶
发表于 2025-3-27 17:02:03
Identifying Minimum-Sized Influential Vertices on Large-Scale Weighted Graphs: A Big Data Perspectivfuzzy set. This approximation allows to divide the whole graph into multiple subgraphs that can be processed independently. Then, for each subgraph, a MapReduce-based greedy algorithm can be designed to identify the minimum-sized influential vertices for the whole graph.
Projection
发表于 2025-3-27 21:33:10
http://reply.papertrans.cn/27/2631/263086/263086_36.png
压倒
发表于 2025-3-27 22:06:08
A Framework for Data Mining and Knowledge Discovery in Cloud Computingnd advantages of the proposed DMCC framework. This study also compares the running times when data mining algorithms are executed in serial and parallel in a cloud environment through DMCC framework. Experimental results show that DMCC greatly decreases the execution times of data mining algorithms.
attenuate
发表于 2025-3-28 04:45:12
http://reply.papertrans.cn/27/2631/263086/263086_38.png
变量
发表于 2025-3-28 07:06:54
Book 2016resents techniques for machine learning for big data, and identifying duplicate records in data repositories; examines enabling technologies and tools for data mining; proposes frameworks for data extraction, and adaptive decision making and social media analysis.
桶去微染
发表于 2025-3-28 14:23:59
David Brown,Mike Herman,Gustavo Nobreis suitable for both complex (Web-level) and simple (device-level) applications. On the variety dimension, the goal is to reduce design-time requirements for interoperability by using structural data matching instead of sharing schemas or media types. In this approach, independently developed applic