[1]黄河燕,曹朝,冯冲.大数据情报分析发展机遇及其挑战[J].智能系统学报,2016,11(6):719-727.[doi:10.11992/tis.201610025]
 HUANG Heyan,CAO Zhao,FENG Chong.Opportunities and challenges of big data intelligence analysis[J].CAAI Transactions on Intelligent Systems,2016,11(6):719-727.[doi:10.11992/tis.201610025]
点击复制

大数据情报分析发展机遇及其挑战

参考文献/References:
[1] GINSBERG J, MOHEBBI M H, PATEL R S, et al. Detecting influenza epidemics using search engine query data[J]. Nature, 2009, 457(7232):1012-1014.
[2] 包昌火. 情报研究方法论[M]. 北京:科学技术文献出版社, 1990. BAO Changhuo. Information research methodology[M]. Beijing:Science and Technology Literature Publishing House, 1990.
[3] WEISS G. A Modern approach to distributed artificial intelligence[J]. IEEE transactions on systems man & cybernetics-part c applications & reviews, 1999, 22(2).
[4] MANYIKA J, CHUI M, BUGHIN J, et al. Big data:the next frontier for innovation, competition, and productivity[R]. McKinsey Global Institute, 2011.
[5] ETEMADPOUR R, MURRAY P, FORBES A G. Evaluating density-based motion for big data visual analytics[C]//Proceedings of IEEE International Conference on Big Data. Washington, DC, USA, 2014:451-460.
[6] SONG Jingkuan, YANG Yang, YANG Yi, et al. Inter-media hashing for large-scale retrieval from heterogeneous data sources[C]//Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data. New York, NY, USA, 2013:785-796.
[7] RAGHUPATHI W, RAGHUPATHI V. Big data analytics in healthcare:promise and potential[J]. Health information science and systems, 2014, 2:3.
[8] PIRES A J M. Big data analytics in healthcare:are end-users ready[D]. Braga:Universidade Católica Portuguesa, 2014.
[9] SHVACHKO K, KUANG Hairong, RADIA S, et al. The hadoop distributed file system[C]//Proceedings of the 2010 IEEE 26th Symposium on Mass Storage Systems and Technologies. Incline Village, NV, USA, 2010:1-10.
[10] ZAHARIA M, CHOWDHURY M, FRANKLIN M J, et al. Spark:cluster computing with working sets[C]//Proceedings of the 2nd USENIX Conference on Hot Topics in Cloud Computing. Berkeley, CA, USA, 2010:10.
[11] JUNG K, KIM K I, JAIN A K. Text information extraction in images and video:a survey[J]. Pattern recognition, 2004, 37(5):977-997.
[12] SODERLAND S. Learning information extraction rules for semi-structured and free text[J]. Machine learning, 1999, 34(1/2/3):233-272.
[13] ZHANG Yongmian, JI Qiang. Active and dynamic information fusion for facial expression understanding from image sequences[J]. IEEE transactions on pattern analysis and machine intelligence, 2005, 27(5):699-714.
[14] SU Xueyuan, SWART G. Oracle in-database hadoop:when mapreduce meets RDBMS[C]//Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data. Scottsdale, AZ, USA, 2012:779-790.
[15] TAHANI H, KELLER J M. Information fusion in computer vision using the fuzzy integral[J]. IEEE transactions on systems, man, and cybernetics, 1990, 20(3):733-741.
[16] WANG Jun, HU Yiming. WOLF-a novel reordering write buffer to boost the performance of log-structured file system[C]//Proceedings of the 1st USENIX Conference on File and Storage Technologies. Monterey, CA, USA, 2002:4.
[17] 孟小峰, 慈祥. 大数据管理:概念、技术与挑战[J]. 计算机研究与发展, 2013, 50(1):146-169. MENG Xiaofeng, CI Xiang. Big data management:concepts, techniques and challenges[J]. Journal of computer research and development, 2013, 50(1):146-169.
[18] WU Xindong, ZHU Xingquan, WU Gongqing, et al. Data mining with big data[J]. IEEE transactions on knowledge and data engineering, 2014, 26(1):97-107.
[19] KOVAR L, GLEICHER M. Automated extraction and parameterization of motions in large data sets[J]. ACM transactions on graphics, 2004, 23(3):559-568.
[20] LAZER D, KENNEDY R, KING G, et al. The parable of Google flu:traps in big data analysis[J]. Science, 2014, 343(6176):1203-1205.
[21] FAN Jianqing, HAN Fang, LIU Han. Challenges of big data analysis[J]. National science review, 2014, 1(2):293-314.
[22] SCHMIDHUBER J. Deep learning in neural networks:an overview[J]. Neural networks, 2015, 61:85-117.
[23] CARLSON A, BETTERIDGE J, KISIEL B, et al. Toward an architecture for never-ending language learning[C]//AAAI 2010 Twenty-Fourth AAAI Conference on Artificial Intelligence. Atlanta, Georgia, USA, 2010:529-573.
[24] BLUM A L, LANGLEY P. Selection of relevant features and examples in machine learning[J]. Artificial intelligence, 1997, 97(1/2):245-271.
[25] JIN Songchang, LIN Wangqun, YIN Hong, et al. Community structure mining in big data social media networks with MapReduce[J]. Cluster computing, 2015, 18(3):999-1010.
[26] TANG Jiliang, LIU Huan. Unsupervised feature selection for linked social media data[C]//Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Beijing, China, 2012:904-912.
[27] CASSIDY A S, MEROLLA P, ARTHUR J V, et al. Cognitive computing building block:a versatile and efficient digital neuron model for neurosynaptic cores[C]//Proceedings of the 2013 International Joint Conference on Neural Networks. Dallas, TX, USA, 2013:1-10.
[28] PREISSL R, WONG T M, DATTA P, et al. Compass:a scalable simulator for an architecture for cognitive computing[C]//Proceedings of the 2012 International Conference on High Performance Computing, Networking, Storage and Analysis. Salt Lake City, UT, USA, 2012:1-11.
[29] KEIM D, QU Huamin, MA K L. Big-data visualization[J]. IEEE computer graphics and applications, 2013, 33(4):20-21.
[30] MEYEROVICH L A, TOROK M E, ATKINSON E, et al. Superconductor:a language for big data visualization[M]. Shenzhen, China:ACM, 2013.
[31] HACHET M, KRUIJFF E. Guest editor’s introduction:special section on the ACM symposium on virtual reality software and technology[J]. IEEE transactions on visualization and computer graphics, 2010, 16(1):2-3.
[32] CHILDS H, BRUGGER E, BONNELL K, et al. A contract based system for large data visualization[C]//Proceedings of VIS 05. IEEE Visualization. Minneapolis, MN, USA, 2005:191-198.
[33] KANOV K, PERLMAN E, BURNS R, et al. I/O streaming evaluation of batch queries for data-intensive computational turbulence[C]//Proceedings of 2011 International Conference for High Performance Computing, Networking, Storage and Analysis. Seattle, WA, USA, 2011:1-10.
[34] FRASCA M, PRABHAKAR R, RAGHAVAN P, et al. Virtual I/O caching:dynamic storage cache management for concurrent workloads[C]//Proceedings of 2011 International Conference on High Performance Computing Networking, Storage and Analysis. Seattle, WA, USA, 2011:1-11.
[35] 张建勋, 古志民, 郑超. 云计算研究进展综述[J]. 计算机应用研究, 2010, 27(2):429-433. ZHANG Jianxun, GU Zhimin, ZHENG Chao. Survey of research progress on cloud computing[J]. Application research of computers, 2010, 27(2):429-433.
[36] WANG Guojun, LIU Qin, WU Jie. Hierarchical attribute-based encryption for fine-grained access control in cloud storage services[C]//Proceedings of the 17th ACM conference on Computer and communications security. Chicago, Illinois, USA, 2010:735-737.
[37] CHANG F, DEAN J, GHEMAWAT S, et al. Bigtable:a distributed storage system for structured data[J]. ACM transactions on computer systems, 2008, 26(2):4.
[38] ARMBRUST M, FOX A, GRIFFITH R, et al. Above the clouds:a Berkeley view of cloud computing[R]. Technical Report No. UCB/EECS-2009-28. Berkeley:EECS Department University of California Berkeley, 2009:50-58.
[39] DEAN J, Ghemawat S. MapReduce:simplified data processing on large clusters[C]//Proceedings of the 6th Conference on Symposium on Opearting Systems Design & Implementation. San Francisco, CA, USA, 2004:107-113.
[40] IQBAL M H, SOOMRO T R. Big data analysis:apache storm perspective[J]. International journal of computer trends and technology, 2015, 19(1):9-14.
[41] WANG Cong, CHOW S S M, WANG Qian, et al. Privacy-preserving public auditing for secure cloud storage[J]. IEEE transactions on computers, 2013, 62(2):362-375.
[42] KATSUNO H, MENDELZON A O. Propositional knowledge base revision and minimal change[J]. Artificial intelligence, 1991, 52(3):263-294.
[43] HOFFART J, SUCHANEK F M, BERBERICH K, et al. YAGO2:a spatially and temporally enhanced knowledge base from Wikipedia[J]. Artificial intelligence, 2013, 194:28-61.
[44] LEHMANN D, MAGIDOR M. What does a conditional knowledge base entail[J]. Artificial intelligence, 1992, 55(1):1-60.
[45] BARBARá D, GARCIA-MOLINA H, PORTER D. The management of probabilistic data[J]. IEEE transactions on knowledge and data engineering, 1992, 4(5):487-502.
[46] KOUBARAKIS M, SKIADOPOULOS S, TRYFONOPOULOS C. Logic and computational complexity for Boolean information retrieval[J]. IEEE transactions on knowledge and data engineering, 2006, 18(12):1659-1666.
相似文献/References:
[1]辛雨璇,闫子飞.基于手绘草图的图像检索技术研究进展[J].智能系统学报,2015,10(2):167.[doi:10.3969/j.issn.1673-4785.201401045]
 XIN Yuxuan,YAN Zifei.Research progress of image retrieval based on hand-drawn sketches[J].CAAI Transactions on Intelligent Systems,2015,10():167.[doi:10.3969/j.issn.1673-4785.201401045]
[2]王德文,孙志伟.一种基于内存计算的电力用户聚类分析方法[J].智能系统学报,2015,10(4):569.[doi:10.3969/j.issn.1673-4785.201411011]
 WANG Dewen,SUN Zhiwei.A method for cluster analysis of electric power consumers based on in-memory computing[J].CAAI Transactions on Intelligent Systems,2015,10():569.[doi:10.3969/j.issn.1673-4785.201411011]
[3]申彦,朱玉全.CMP上基于数据集划分的K-means多核优化算法[J].智能系统学报,2015,10(4):607.[doi:10.3969/j.issn.1673-4785.201411036]
 SHEN Yan,ZHU Yuquan.An optimized algorithm of K-means based on data set partition on CMP systems[J].CAAI Transactions on Intelligent Systems,2015,10():607.[doi:10.3969/j.issn.1673-4785.201411036]
[4]马世龙,乌尼日其其格,李小平.大数据与深度学习综述[J].智能系统学报,2016,11(6):728.[doi:10.11992/tis.201611021]
 MA Shilong,WUNIRI Qiqige,LI Xiaoping.Deep learning with big data: state of the art and development[J].CAAI Transactions on Intelligent Systems,2016,11():728.[doi:10.11992/tis.201611021]
[5]苗夺谦,张清华,钱宇华,等.从人类智能到机器实现模型——粒计算理论与方法[J].智能系统学报,2016,11(6):743.[doi:10.11992/tis.201612014]
 MIAO Duoqian,ZHANG Qinghua,QIAN Yuhua,et al.From human intelligence to machine implementation model: theories and applications based on granular computing[J].CAAI Transactions on Intelligent Systems,2016,11():743.[doi:10.11992/tis.201612014]
[6]严新平,柳晨光.智能航运系统的发展现状与趋势[J].智能系统学报,2016,11(6):807.[doi:10.11992/tis.201605007]
 YAN Xinping,LIU Chenguang.Review and prospect for intelligent waterway transportation system[J].CAAI Transactions on Intelligent Systems,2016,11():807.[doi:10.11992/tis.201605007]
[7]许立波,潘旭伟,袁平,等.知识智能涌现创新:概念、体系与路径[J].智能系统学报,2017,12(1):47.[doi:10.11992/tis.201610014]
 XU Libo,PAN Xuwei,YUAN Ping,et al.Knowledge innovation by intelligent emergence—concept, framework and its pathway[J].CAAI Transactions on Intelligent Systems,2017,12():47.[doi:10.11992/tis.201610014]
[8]何明,常盟盟,刘郭洋,等.基于SQL-on-Hadoop查询引擎的日志挖掘及其应用[J].智能系统学报,2017,12(5):717.[doi:10.11992/tis.201706016]
 HE Ming,CHANG Mengmeng,LIU Guoyang,et al.Log mining and application based on sql-on-hadoop query engine[J].CAAI Transactions on Intelligent Systems,2017,12():717.[doi:10.11992/tis.201706016]
[9]马钰,张岩,王宏志,等.面对智能导诊的个性化推荐算法[J].智能系统学报,2018,13(3):352.[doi:10.11992/tis.201711036]
 MA Yu,ZHANG Yan,WANG Hongzhi,et al.A personalized recommendation algorithm for intelligent guidance[J].CAAI Transactions on Intelligent Systems,2018,13():352.[doi:10.11992/tis.201711036]
[10]牛德姣,刘亚文,蔡涛,等.基于递归神经网络的跌倒检测系统[J].智能系统学报,2018,13(3):380.[doi:10.11992/tis.201710013]
 NIU Dejiao,LIU Yawen,CAI Tao,et al.Fall detection system based on recurrent neural network[J].CAAI Transactions on Intelligent Systems,2018,13():380.[doi:10.11992/tis.201710013]

备注/Memo

收稿日期:2016-10-24。
基金项目:国家重点研发计划项目(2016YFB1000902).
作者简介:黄河燕,女,1963年生,教授。任中国人工智能学会和中国中文信息学会副理事长。主要研究方向为机器翻译、自然语言处理、社会计算。曾获国家科技进步一等奖、中国科学院科技进步一等奖和北京市科学技术一等奖等奖励。发表学术论文多篇;曹朝,男,1982年生,副研究员,博士,中国计算机学会数据库专委会委员。主要研究方向为数据库管理系统、分布式系统、智能信息处理。发表学术论文多篇;冯冲,男,1977年生,副研究员,博士,中文信息学会社会媒体处理专委会委员、语言与知识计算专委会委员。主要研究方向为网络信息抽取和多语机器翻译。曾获部级科技奖励3项。发表学术论文30余篇、编著1部,申请专利10余项。
通讯作者:黄河燕.E-mail:hhy63@bit.edu.cn.

更新日期/Last Update: 1900-01-01
Copyright © 《 智能系统学报》 编辑部
地址:(150001)黑龙江省哈尔滨市南岗区南通大街145-1号楼 电话:0451- 82534001、82518134 邮箱:tis@vip.sina.com