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大数据及其对地矿分析测试工作的启示——以贵州地质矿产中心实验室为例 被引量：4

Big Data and Its Revelation for the Work of Geological Mining Analysis Test:Case Study of Guizhou Central Laboratory of Geology and Mineral Resources
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摘要 大数据已经受到越来越多的关注,大数据时代即将到来。在介绍大数据的内涵基础上,分析大数据的特征和时代价值,探讨其带给社会经济发展的意义。大数据时代将对地质矿产实验室的分析测试数据库建设和管理工作带来了新的机遇。 Big data has attracted more and more attention, and big data era is coming. Based on the introduction of the connotation of big data, this article analyzes the characteristics and time value of big data. Its significance for social and economic development is discussed. Big data era will bring new opportunity for the geology and mineral resources laboratory analysis and test database construction and the management.
作者 吴梅
机构地区 贵州地质矿产中心实验室
出处 《价值工程》 2014年第17期234-235,共2页 Value Engineering
关键词 大数据 数据库 地质矿产 分析测试 big data database geology and mineral resources analysis and test
分类号 G203 [文化科学—传播学]
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参考文献3

二级参考文献78

  • 1Big data. Nature, 2008, 455(7209): 1-136.
  • 2Dealing with data. Science,2011,331(6018): 639-806.
  • 3Holland J. Emergence: From Chaos to Order. RedwoodCity,California: Addison-Wesley? 1997.
  • 4Anthony J G Hey. The Fourth Paradigm: Data-intensiveScientific Discovery. Microsoft Research, 2009.
  • 5Phan X H, Nguyen L M,Horiguchi S. Learning to classifyshort and sparse text Web with hidden topics from large-scale data collections//Proceedings of the 17th InternationalConference on World Wide Web. Beijing, China,2008:91-100.
  • 6Sahami M, Heilman T D. A web-based kernel function formeasuring the similarity of short text snippets//Proceedingsof the 15th International Conference on World Wide Web.Edinburgh, Scotland, 2006: 377-386.
  • 7Efron M, Organisciak P,Fenlon K. Improving retrieval ofshort texts through document expansion//Proceedings of the35th International ACM SIGIR Conference on Research andDevelopment in Information Retrieval. Portland, OR, USA,2012: 911-920.
  • 8Hong L,Ahmed A, Gurumurthy S,Smola A J, Tsioutsiou-liklis K. Discovering geographical topics in the twitterstream//Proceedings of the 21st International Conference onWorld Wide Web(WWW 2012). Lyon, France, 2012:769-778.
  • 9Pozdnoukhov A,Kaiser C. Space-time dynamics of topics instreaming text//Proceedings of the 3rd ACM SIGSPATIALInternational Workshop on Location-Based Social Networks.Chicago-IL,USA, 2011: 1-8.
  • 10Sun Yizhou,Norick Brandon, Han Jiawei, Yan Xifeng, YuPhilip S,Yu Xiao. Integrating meta-path selection with user-guided object clustering in heterogeneous information net-works/ /Proceedings of the 18th ACM SIGKDD InternationalConference on Knowledge Discovery and Data Mining.Beijing, China, 2012: 1348-1356.

共引文献852

同被引文献41

  • 1张建.大数据点金大油气[J].中国石油企业,2014(4):69-71. 被引量：5
  • 2朱月霞,侯建光.基于大数据的地质数据存储与管理研究[C]//江苏省测绘地理信息学会2014年学术年会论文集,2014.
  • 3每日经济新闻.我国2014年进口石油3亿吨,对外依存度逼近六成[EB/OL].http://finance.eastmoney.com/news/1345,20150114467384774.htm.
  • 4第一财经.我国2014年天然气对外依存度32.2%,[EB/0L].2015.http://www.yicai.com/news/2015/01/4065535.html.
  • 5余永红,刘鸿儒,徐洁磐.基于OMNIX面向对象数据库管理系统的石油数据银行的研究[C/OL].第十七届全国数据库学术会议.保定:5.
  • 6辛胜德.石油数据银行产生及其发展[N].中国石油报,2002-6-3(2).
  • 7Perrons, R.K.,J.W. Jensen. Data as an asset:what the oil and gas sector can learn from other industries about "Big Data"[J].Energy Policy, 2015.81:p. 117-121.
  • 8K Holdaway. Harness oil and analytics:optimize exploration gas big data with and production with data driven models[M].2014: John Wiley & Sons.
  • 9Big data solutions & analytics in upstream oil and gas industry[C].2015. Oslo, Norway.
  • 10Gas, D.A.I. 2nd data and information management in oil and gas[C].2015. Abu Dhabi, The United Arab Emirates.

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价值工程
2014年 第17期

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