计算机科学 ›› 2020, Vol. 47 ›› Issue (6): 66-73.doi: 10.11896/jsjkx.191000072
刘纪芹1, 史开泉2
LIU Ji-qin1, SHI Kai-quan2
摘要: 文中给出了通过大数据分解、融合生成的大数据分解-融合以及大数据距离;利用这些概念,给出了大数据并-交分解定理以及大数据交-并分解定理与它们的属性合取关系、大数据融合的智能生成定理与大数据融合的距离关系、大数据分解-融合的识别准则与大数据分解-融合获取的智能算法与算法的过程,以及这些理论结果在大数据分解-融合智能获取的应用。文中给出了∧型大数据新的特征,∧型大数据是利用P-集合模型得到的。
中图分类号:
[1]SHI K Q.Big data structure-logic characteristics and big data law [J].Journal of Shandong University (Natural Science),2019,54(2):1-29. [2]WANG F Y,CARLEY K M,ZENG D,et al.Social computing:from social informatics to social intelligence [J].IEEE Intelligent systems,2007,22(2):79-83. [3]ZHANG N,WANG F Y,ZHU F,et al.DynaCAS:Computational experiments and decision support for ITS [J].IEEE Intelligent Systems,2008,23(6):19-23. [4]WANG F Y.Parallel control and management for intelligent transportation systems:Concepts,architectures,and applications[J].IEEE Transactions on Intelligent Transportation Systems,2010,11(3):630-638. [5]WANG F Y.Scanning the issue and beyond:Parallel driving with software vehicular robots for safety and smartness [J].IEEE Transactions on Intelligent Transportation Systems,2014,15(4):1381-1387. [6]LV Y,DUAN Y,KANG W,et al.Traffic flow prediction with big data:A deep learning approach [J].IEEE Trans.Intelligent Transportation Systems,2015,16(2):865-873. [7]LV Y,ZHANG X,KANG W,et al.Managing emergency traffic evacuation with a partially random destination allocation strategy:a computational-experiment-based optimization approach[J].IEEE Trans.Intelligent Transportation Systems,2015,16(4):2182-2191. [8]YUAN Y,WANG F Y,ZENG D.Developing a cooperative bidding framework for sponsored search markets-An evolutionary perspective [J].Information Sciences,2016,369:674-689. [9]WANG F Y.The emergence of intelligent enterprises:From CPS to CPSS [J].IEEE Intelligent Systems,2010,25(4):85-88. [10]GOODHOPE K,KOSHY J,KREPS J,et al.Building LinkedIn’s real-time activity data pipeline [J].IEEE Data Eng.Bull.,2012,35(2):33-45. [11]MCKUSICK K,QUINLAN S.GFS:evolution on fastforward [J].Communications of the ACM,2010,53(3):42-49. [12]COOPER B F,RAMAKRISHNAN R,SRIVASTAVA U,et al.PNUTS:Yahoo!’s hosted data serving platform [J].Procee-dings of the VLDB Endowment,2008,1(2):1277-1288. [13]MELNIK S,GUBAREV A,LONG J J,et al.Dremel:interactive analysis of web-scale datasets [J].Proceedings of the VLDB Endowment,2010,3(1/2):330-339. [14]BU Y,HOWE B,BALAZINSKA M,et al.HaLoop:efficient iterative data processing on large clusters [J].Proceedings of the VLDB Endowment,2010,3(1/2):285-296. [15]LAM W,LIU L,PRASAD S T S,et al.Muppet:MapReducestyle processing of fast data [J].Proceedings of the VLDB Endowment,2012,5(12):1814-1825. [16]CHEN S.CHEETAH:a high performance,custom data warehouse on top of MapReduce [J].Proceedings of the VLDB Endowment,2010,3(1/2):1459-1468. [17]CANIM M,MIHAILA G A,BHATTACHARJEE B,et al.SSD bufferpool extensions for database systems [J].Proceedings of the VLDB Endowment,2010,3(1/2):1435-1446. [18]LUO T,LEE R,MESNIER M,et al.Storage-DB:heterogeneity-aware data management to exploit the full capability of hybrid storage systems [J].Proceedings of the VLDB Endowment,2012,5(10):1076-1087. [19]WONG P C,SHEN H W,JOHNSON C R,et al.The top 10 challenges in extreme-scale visual analytics[J].IEEE computer graphics and applications,2012,32(4):63-67. [20]PIKE R,DORWARD S,GRIESEMER R,et al.Interpreting the data:parallel analysis with Sawzall [J].Scientific Programming,2005,13(4):277-298. [21]SHI K Q.P-sets [J].Journal of Shandong University (Natural Science),2008,43(11):77-84. [22]SHI K Q.P-sets and its applications [J].Advances in Systems Science and Applications,2009,9(2):209-219. [23]SHI K Q.P-sets and its applied characteristics [J].Computer Science,2010,37(8):1-8. [24]SHI K Q.P-reasoning and P-reasoning discoveryidentification of information [J].Computer Science,2011,38(7):1-9. [25]SHI K Q.P-sets,inverse P-sets and the intelligent fusionfilter identification of information [J].Computer Science,2012,39(4):1-13. [26]FAN C X,LIN H K.P-sets and the reasoningidentification of disaster information [J].International Journal of Convergence Information Technology,2012,7(1):337-345. [27]LIN H K,FAN C X.The dual form of P-reasoning and identification of unknown attribute [J].International Journal of Digital Content Technology and its Applications,2012,6(1):121-131. [28]ZHANG L,CUI Y Q,SHI K Q.Outer P-sets and data internal recovery [J].Systems Engineering and Electronics,2010,32(6):1233-1238. [29]WANG Y,GENG H Q,SHI K Q.P-sets and dependencediscovery of dynamic information [J].Systems Engineering and Electronics,2011,33(9):2035-2038. [30]LI Y Y,LIN H K,SHI K Q.Characteristics of data discrete interval and data discovery-application [J].Systems Engineering and Electronics,2011,33(10):2258-2262. [31]ZHANG L,TANG J H,SHI K Q.The fusion of internal packet information and its feature of attribute conjunction [J].Journal of Shandong University(Natural Science),2014,49(2):93-97. [32]SHI K Q,ZHANG L.Internal P-set and data outerrecovery[J].Journal of Shandong University (Natural Science),2009,44(4):8-14. [33]ZHANG G Y,ZHOU H Y,SHI K Q.P-sets and the recoveryidentification double [J].Systems Engineering and Electronics,2010,32(9):1919-1924. [34]ZHANG L,REN X F.P-sets and (f,f)-heredity [J].Quantitative Logic and Soft Computing,2010,2(1):735-743. [35]ZHANG L,XIU M,SHI K Q.P-sets and application of internal-outer data circle [J].Quantitative Logic and Soft Computing,2010,2(1):581-591. [36]QIU Y F,CHEN B H.f-model generated by P-sets [J].Quantitative Logic and Soft Computing,2010,2(1):613-620. [37]LI Y Y,ZHANG L,SHI K Q.Generation and recovery of compressed data and redundant data[J].Quantitative Logic and Soft Computing,2010,2(1):661-671. [38]XIU M,SHI K Q,ZHANG L.P-sets and F-data selection-discovery [J].Quantitative Logic and Soft Computing,2010,2(1):791-799. [39]ZHAO S L,FAN C X,SHI K Q.Outer P-information generation and its reasoning-searching discovery[J].Journal of Shandong University(Natural Science),2012,47(1):99-104. [40]ZHAO S L,WU S L,SHI K Q.Internal Preasoning information recovery and attribute hiding searching discovery [J].Computer Science,2013,40(4):209-213. [41]SHI K Q.Function P-sets[J].Journal of Shandong University (Natural Science),2011,46(2):62-69. [42]SHI K Q.Function P-sets[J].International Journal of Machine Learning and Cybernetics,2011,2(4):281-288. [43]SHI K Q.P-information law intelligent fusion and soft information image intelligent generation[J].Journal of Shandong University(Natural Science),2014,49(4):1-17. [44]TANG J H,ZHANG L,SHI K Q.Intelligent fusion of information law and its inner separation[J].Computer Science,2015,42(2):204-209. [45]LIN R,FAN C X.Function P-sets and dynamic characteristics of information law[J].Journal of Shandong University (Natural Science),2012,47(1):121-126. [46]REN X F,ZHANG L,SHI K Q.Two types of dynamic information law models and their applications in information camouflage and risk identification[J].Computer Science,2018,45(9):230-236. [47]CHEN B H,ZHANG L,SHI K Q.Intelligent dynamic fusion of packet information and the intelligent state recognition of information law[J].Journal of Shandong University (Natural Science),2018,53(2):83-87. [48]TANG J H,ZHANG L,SHI K Q,et al.Outer Pinformation law reasoning andits application in intelligent fusion and separating of information law[J].Microsystem Technologies,2018,24(10):4389-4398. [49]SHI K Q.P-augmented matrix and dynamic intelligent discovery-identification of information[J].Journal of Shandong University (Natural Science),2015,50(10):1-12. [50]LIN H K,FAN C X.Embedding camouflage of inverse P-information and application[J].International Journal of Convergence Information and Technology,2012,7(20):471-480. [51]FAN C X,HUANG S L.Inverse P-reasoning discovery identification of inverse P-information[J].International Journal of Di-gital Content Technology and its Applications,2012,6(20):735-744. [52]SHI K Q.Function inverse P-sets and the hiding information generated by function inverse P-information law fusion[C]// Proceedings of the 13th IFIP WG 6.11 Conference on e-Business,e-Services,and e-Society,Sanya,China,2014:224-237. [53]GUO H L,REN X F,ZHANG L.Relationships between dynamic data mining and P-augmented matrix[J].Journal of Shandong University (Natural Science),2016,51(8):105-110. [54]GUO H L,CHEN B H,TANG J H.Inverse P-sets and intelligent fusion mining-discovery of information[J].Journal of Shandong University (Natural Science),2013,48(8):97-103,110. [55]ZHANG L,REN X F,SHI K Q.The dynamic segmentation characteristics of P-augmented matrix and the dynamic intelligent acquisition of P-information[J].International Journal of Applied Decision Sciences,2016,9(4):413-425. [56]ZHANG L,REN X F,SHI K Q,et al.Inverse packet matrix reasoning model-based the intelligent dynamic separation and acquisition of educational information[J].Microsystem Technologies,2018,24(10):4415-4421. [57]REN X F,ZHANG L,SHI K Q,et al.Inverse P-augmented matrix method-based the dynamic findings of unknown information[J].Microsystem Technologies,2018,24(10):4187-4192. [58]ZHANG L,REN X F,SHI K Q.Inverse P-information law models and the reality-camouflage intelligent transformations of information image[C]//Proceedings of the 2016 International Conference on Network and Information Systems for Compu-ters,Washington:IEEE,2016:337-341. [59]ZHANG L,REN X F,SHI K Q.Inverse P-data models and data intelligent separation[C]//Proceedings of the 2016 International Conference on Electronic Information Technology and Intellectualization,DOI:10.12783/dtcse/iceiti2016/6107,2016. [60]REN X F,ZHANG L,SHI K Q.Surplusdeficiency of cardinal number and inverse P-augmented matrices[J].Journal of Shandong University (Natural Science),2015,50(10):13-18,26. [61]ZHANG L,REN X F.Surplus-deficient theorem of cardinal number and data internal-outer miningseparation [J].Journal of Shandong University (Natural Science),2015,50(8):90-94. [62]GUO H L,ZHANG L.Data separation and its attribute state characteristics [J].Journal of Shandong University (Natural Science),2017,52(12):89-94. [63]TANG J H,CHEN B H.Intelligent fusion of internal inverse packet information and expansion relationship of attribute disjunction[J].Journal of Shandong University (Natural Science),2014,49(2):89-92,97. [64]ZHANG L,REN X F,SHI K Q.Intelligent switchcamouflage of information laws and P-law augmented matrices [J].Journal of Shandong University (Natural Science),2016,51(8):90-97. [65]REN X F,ZHANG L,SHI K Q.Boundary Characteristics of Inverse P-sets and System Condition Monitoring[J].Computer Science,2016,43(10):211-213,255. [66]REN X F,ZHANG L.Perturbation theorems of inverse P-sets and perturbation-based data mining[J].Journal of Shandong University (Natural Science),2016,51(12):54-60. [67]LIU J Q,ZHANG H Y.Information P-dependence and P-dependence mining-sieving [J].Computer Science,2018,45(7):202-206. [68]SHI K Q,YAO B X.Function S-rough sets and law identification[J].Science in China E:Information Science,2008,38(4):553-564. [69]SHI K Q,ZHAO J L.Function S-rough sets and security-authentication of hiding law[J].Science in China E:Information Science,2008,38(8):1234-1243. [70]SHI K Q,YAO B X.Function S-rough sets and law identification[J].Science in China F:Information Science,2008,51(5):499-510. [71]SHI K Q,ZHAO J L.Function S-rough sets and security-authentication of hiding law[J].Science in China F:information Sciences,2008,51(7):924-935. |
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