26, NO. 1, JANUARY 2014 97 Data Mining with Big Data Xindong Wu, Fellow, IEEE, Xingquan Zhu, Senior Member, IEEE, Gong-Qing Wu, and Wei Ding, Senior Member, IEEE Abstract—Big Data concern large-volume, complex, growing data sets with multiple, autonomous sources. With the fast ...
dataminingwithbig 系统标签: databigminingskatweetsquintillion DataMiningwithBigData XindongWu,Fellow,IEEE,XingquanZhu,SeniorMember,IEEE, Gong-QingWu,andWeiDing,SeniorMember,IEEE Abstract—BigDataconcernlarge-volume,complex,growingdatasetswithmultiple,autonomoussources.Withthefastdevelopment ofnetworking,datastorage...
大数据挖掘 论文翻译:Data mining with big data,原文:WuX,ZhuX,WuGQ,etal.Dataminingwithbigdata[J].IEEEtransactionsonknowledgeanddataengineering,2013,26(1):97-107.使用大数据进行数据挖掘Xi
Mining big data streams with apache SAMOA In this talk, we present Apache SAMOA, an open-source platform for mining big data streams with Apache Flink, Storm and Samza. Real time analytics is becoming the fastest and most efficient way to obtain useful knowledge from what is hap... A Bifet...
Review on "Data Mining with Big Data" --Big Data relates large-volume, complex, increasing data sets with multiple independent sources. With the rapid evolution of data, data storage and the networking collection capability, Big Data are now speedily expanding in all science... V Yenkar,PM ...
Introducing the new knowledge of Big Data for belief apprehension of large-volume, complex, growing data sets with several autonomous sources. HACE theorem that characterizes the features of big data revolution and perform the operation in data mining perspective. Big Data e-Health Service application...
计算机专业英语Unit 11 Data Mining and Big Data 计算机专业英语Unit11DataMiningandBigData BackgroundKnowledge背景知识 ❖近年来，数据挖掘引起了信息产业界的极大关注，其主要原因是存在大量数据，可以广泛使用，并且迫切需要将这些数据转换成有用的信息和知识。获取的信息和知识可以广泛用于各种应用，包括商务管理，...
Data Mining with Big Data In an Information technology world, the ability to effectively process massive datasets has become integral to a broad range of scientific and other academ... R Sowmya,KR Suneetha - IEEE 被引量: 215发表: 2017年 A Parallel Distributed Weka Framework for Big Data ...
I provide definitions of the terms and identify the "four Vs" of big data: volume, variety, velocity, and veracity. I summarize the various kinds of problems that are involved in data mining and the approaches that are necessary when the data is too large to store in memory, arriving too...
The "Big data" ecosystem at LinkedIn The use of large-scale data mining and machine learning has proliferated through the adoption of technologies such as Hadoop, with its simple programming s... R Sumbaly,J Kreps,S Shah - ACM 被引量: 91发表: 2013年 Big data visualization: Tools and ...