期刊文献+

基于高职院校教学督导共享平台大数据分析研究 被引量:3

Big Data Analysis and Research Based on Vocational College Teaching Supervision Sharing Platform
下载PDF
导出
摘要 近年来随着人类生活全面向互联网转移,迎来了大数据时代。众所周知,大数据已经不简简单单是数据大的事实了,最重要的是对大数据进行分析,获取很多智能的,深入的,有价值的信息。本文基于高职院校教学督导共享平台大数据进行分析研究,通过大数据分析提供有价值的决定性因素,提高高职院校教育教学质量。 In recent years,we has ushered into the era of big data with comprehensive transfer to internet. It is well known to all,there is a fact that big data does not simply mean data is big,while the most important reality is to make analysis of big data,to obtain smart, in-depth and valuable information through analysis. This paper makes an analysis of the big data from vocational colleges teaching supervision sharing platform, to offer valuable decisive factors, and to improve the teaching quality of vocational college education.
作者 杨居义
出处 《南京工业职业技术学院学报》 2016年第2期33-36,共4页 Journal of Nanjing Institute of Industry Technology
基金 四川省教育厅研究课题"高职院校教学督导共享平台大数据分析研究"(编号:13SB0476) 四川省高等职业教育研究中心研究课题"利用大数据创新教育督导理念与制度研究"(编号:GZY11B17)
关键词 大数据 数据分析 高职院校 教学督导 big data data analysis vocational colleges teaching supervision
  • 相关文献

参考文献4

二级参考文献94

  • 1胡雄伟,张宝林,李抵飞.大数据研究与应用综述(上)[J].标准科学,2013(9):29-34. 被引量:44
  • 2韩少锋,陈立潮.数据挖掘技术及应用综述[J].机械管理开发,2006,21(2):23-24. 被引量:11
  • 3Zhou MQ, Zhang R, Zeng DD, Qian WN, Zhou AY. Join optimization in the MapReduce environment for column-wise data store. In: Fang YF, Huang ZX, eds. Proc. of the SKG. Ningbo: IEEE Computer Society, 2010.97-104. [doi: 10.1109/SKG.2010.18].
  • 4Afrati FN, Ullman JD. Optimizing joins in a Map-Reduce environment. In: Manolescu I, Spaecapietra S, Teubner J, Kitsuregawa M, Leger A, Naumann F, Ailamaki A, Ozcan F, eds. Proc. of the EDBT. Lausanne: ACM Press, 2010. 99-110. [doi: 10.1145/ 1739041.1739056].
  • 5Sandholm T, Lai K. MapReduce optimization using regulated dynamic prioritization. In: Douceur JR, Greenberg AG, Bonald T, Nieh J, eds. Proc. of the SIGMETRICS. Seattle: ACM Press, 2009. 299-310. [doi: 10.1145/1555349.1555384].
  • 6Hoefler T, Lumsdaine A, Dongarra J. Towards; efficient MapReduce using MPI. In: Oster P, ed. Proc. of the EuroPVM/MPI. Berlin: Springer-Verlag, 2009. 240-249. [doi: 10.100'7/978-3-642-03770-2_30].
  • 7Nykiel T, Potamias M, Mishra C, Kollios G, Koudas N. MRShare: Sharing across multiple queries in MapReduce. PVLDB, 2010, 3(1-2):494-505.
  • 8Kambatla K, Rapolu N, Jagannathan S, Grama A. Asynchronous algorithms in MapReduce. In: Moreira JE, Matsuoka S, Pakin S, Cortes T, eds. Proc. of the CLUSTER. Crete: IEEE Press, 2010. 245-254. [doi: 10.1109/CLUSTER.2010.30].
  • 9Polo J, Carrera D, Becerra Y, Torres J, Ayguad6 E, Steinder M, Whalley I. Performance-Driven task co-scheduling for MapReduce environments. In: Tonouchi T, Kim MS, eds. Proc. of the 1EEE Network Operations and Management Symp. (NOMS). Osaka: IEEE Press, 2010. 373-380. [doi: 10.1109/NOMS.2010.5488494].
  • 10Zaharia M, Konwinski A, Joseph AD, Katz R, Stoica I. Improving MapReduce performance in heterogeneous environments. In: Draves R, van Renesse R, eds. Proc. of the ODSI. Berkeley: USENIX Association, 2008.29-42.

共引文献715

同被引文献10

引证文献3

二级引证文献4

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部