计算机科学 ›› 2022, Vol. 49 ›› Issue (12): 185-194.doi: 10.11896/jsjkx.211100080
李爱华1, 续维佳1, 石勇2,3
LI Ai-hua1, XU Wei-jia1, SHI Yong2,3
摘要: 商务智能与分析(BI&A)3.0的出现和信息融合应用场景的拓宽增强了数据融合在商务智能研究中的重要性。越来越多经济和管理领域的研究运用了融合的思想和方法,数据融合在这些领域的应用表现出了不同于传统信息融合的特点。从信息融合和BI&A出发,提出了多源异构大数据背景下基于数据融合视角的BI&A新内涵,突出了数据融合在商务智能分析过程中的重要性。基于WSR系统科学方法论构建了商务智能分析“数据、信息、知识”的融合架构,使数据融合能更好地应用于经济、金融和管理等领域,为从海量多源异构数据中获取知识提供了科学依据,有利于更有效的商务智能系统的研发和实现。
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[1]WALTZ E,LLINAS J.Multi sensor data fusion[M].London:Artech House Radar Library,1990. [2]WHITE J F E.A model for data fusion[C]//Proceedings of the 1st National Symposium on Sensor Fusion.1988:149-158. [3]DING Y,YU X,ZHANG J,et al.Application of linear predictive coding and data fusion process for target tracking by Doppler Through-Wall Radar[J].IEEE Transactions on Microwave Theory and Techniques,2018,67(3):1244-1254. [4]SUSPERREGI L,ARRUTI A,JAUREGI E,et al.Fusing multiple image transformations and a thermal sensor with kinect to improve person detection ability[J].Engineering Applications of Artificial Intelligence,2013,26(8):1980-1991. [5]SHEN H,WU J,CHENG Q,et al.A spatiotemporal fusion based cloud removal method for remote sensing images with land cover changes[J].IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,2019,12(3):862-874. [6]LI K F.Smart home technology for telemedicine and emergency management[J].Journal of Ambient Intelligence and Huma-nized Computing,2013,4(5):535-546. [7]ATAT R,LIU L,WU J,et al.Big data meet cyber-physical systems:A panoramic survey[J].IEEE Access,2018,6:73603-73636. [8]NALLAGONDA S.Data fusion-aided cognitive radio networkover generalised fading channels[J].Electronics Letters,2019,55(5):285-287. [9]WALD L.Some terms of reference in data fusion[J].IEEETransactions on Geoscience and Remote Sensing,1999,37(3):1190-1193. [10]BLACKMAN S,POPOLI R.Design and analysis of moderntracking systems[M].London:Artech House Publishers,1999. [11]CHEN K W,ZHANG Z P,LONG J.Multisource information fusion:key issues,research progress and new trends[J].Computer Science,2013,40(8):6-13. [12]DONG Z R.Information fusion[J].Command Control & Simulation,2001,23(7):27-36. [13]FIGINI S,GIUDICI P.Statistical merging of rating models[J].Journal of the Operational Research Society,2011,62(6):1067-1074. [14]PADILLA W R,GARCÍA J,MOLINA J M.Knowledge extraction and improved data fusion for sales prediction in local agricultural markets[J/OL].Sensors,2019,19(2):286.https://doi.org/10.3390/s19020286. [15]FRANCESCHINI F,MAISANO D.Checking the consistency of the solution in ordinal semi-democratic decision-making problems[J/OL].Omega,2015,57:188-195. https://doi.org/10.1016/j.omega.2015.04.014. [16]PENG D L,WEN C L,XUE A K.Theory and application of multi-sensor and multi-source information Fusion[M].Xi’an:Xidian University,2010. [17]ZHAO J,CUI Z S,XU J M,et al.The essence and core techno-logy of information fusion[J] Command Control & Simulation,2003,25(8):38-42. [18]ZHAO Z G,LI J L,WANG K.The concept,structure and efficiency of battlefield situation assessment[J].Journal of China Academy of Electronics and Information Technology,2010,5(3):226-230. [19]DE VIN L J,HOLM M,NG A.The information fusion JDL-U model as a reference model for virtual manufacturing[J].Robo-tics and Computer-Integrated Manufacturing,2010,26(6):629-638. [20]HARRIS C J,BAILEY A,DODD T J.Multi-Sensor data fusion in defence and aerospace[J].Aeronautical Journal,1998,102(1015):229-244. [21]BEDWORTH M,O'BRIEN J.The Omnibus model:a new model of data fusion?[J].Aerospace & Electronic Systems Magazine IEEE,2000,15(4):30-36. [22]BLASCH E P,BRETON R,VALIN P,et al.User information fusion decision making analysis with the C-OODA model[C]//14th International Conference on Information Fusion.New York:IEEE Press,2011:1-8. [23]LIGGINS M,HALL D,LLINAS J.Handbook of multisensordata fusion:theory and practice(Second Edition)[M].New York:CRC Press,2008. [24]SHAHBAZIAN E,BLODGETT D,LABBÉ P.The extended OODA model for data fusion systems[C]//The 4th International Conference on Information Fusion.2001. [25]WANG R,JI W,LIU M,et al.Review on mining data from multiple data sources[J/OL].Pattern Recognition Letters,2018,109:120-128.https://doi.org/10.1016/j.patrec.2018.01.013. [26]ESCAMILLA-AMBROSIO P J,MORT N.A hybrid Kalman filter-fuzzy logic architecture for multisensor data fusion[C]//Proceeding of the 2001 IEEE International Symposium on Intelligent Control(ISIC'01)(Cat.No.01CH37206).New York:IEEE Press,2001:364-369. [27]DU H,LV F,LI S,et al.Study of fault diagnosis method based on data fusion technology[J/OL].Procedia Engineering,2012,29:2590-2594.https://doi.org/10.1016/j.proeng.2012.01.356 [28]RÖVID A,REMELI V.Towards raw sensor fusion in 3D object detection[C]//IEEE 17th World Symposium on Applied Machine Intelligence and Informatics(SAMI).New York:IEEE Press,2019:293-298. [29]LIANG M,YANG B,WANG S,et al.Deep continuous fusionfor multi-sensor 3d object detection[C]//Proceedings of the European Conference on Computer Vision(ECCV).Munich:Springer,2018:641-656. [30]KUZNETSOVA P,ORDONEZ V,BERG T L,et al.TRE-ETALK:composition and compression of trees for image descriptions[J].Transactions of the Association for Computational Lingus,2014,2(9):351-362. [31]DU Q,XU H,MA Y,et al.Fusing infrared and visible images of different resolutions via total variation model[J/OL].Sensors,2018,18(11):3827.https://doi.org/10.3390/s18113827. [32]CORONA I,GIACINTO G,MAZZARIELLO C,et al.Information fusion for computer security:State of the art and open issues[J].Information Fusion,2009,10(4):274-284. [33]LIU P F,ZHANG P L,ZHANG J,et al.Subject oriented Web information fusion model[J].Library and Information Service,2011,55(8):40-43. [34]ALVES S F R,ROSARIO J M,FERASOLI F H,et al.Conceptual bases of robot navigation modeling,control and applications in Robot Navigation[M].IntechOpen Access Publisher,2011. [35]LATHUILIÈRE S,MASSÉ B,MESEJO P,et al.Deep rein-forcement learning for audio-visual gaze control[C]//2018 IEEE/RSJ International Conference on Intelligent Robots and Systems(IROS).Madrid:IEEE Press,2018:1555-1562. [36]DEEN M J.Information and communications technologies forelderly ubiquitous healthcare in a smart home[J].Personal Ubiquitous Comput,2015,19(3/4):573-599. [37]JAMES A P,DASARATHY B V.Medical image fusion:A survey of the state of the art[J/OL].Information Fusion,2014,19:4-19.https://doi.org/10.1016/j.inffus.2013.12.002. [38]LIANG X,HU P,ZHANG L,et al.MCFNet:Multi-layer concatenation fusion network for medical images fusion[J].IEEE Sensors Journal,2019,19(16):7107-7119. [39]HANNAN B,ZHANG X,SETHARES K.IHANDs:Intelligent health advising and decision-support agent[C]//2014 IEEE/WIC/ACM International Joint Conferences on Web Intelligence(WI) and Intelligent Agent Technologies(IAT).New York:IEEE Press,2014,3:294-301. [40]CHEN H,CHIANG R H L,STOREY V C.Business intelli-gence and analytics:from big data to big impact[J].MIS Quarterly,2012,36(12):1165-1188. [41]ADOMAVICIUS G,TUZHILIN A.Toward the next generation of recommender systems:a survey of the state-of-the-art and possible extensions[J].IEEE Transactions on Knowledge and Data Engineering,2005,17(6):734-749. [42]JOHNSON J,NG Y.Enhancing long tail item recommendations using tripartite graphs and Markov process[C]//Proceedings of the International Conference on Web Intelligence.New York:ACM,2017:761-768. [43]CHEN H.AI,E-government,and Politics 2.0[J].IEEE Intelligent Systems,2009,24(5):64-86. [44]HANAUER D A,ZHENG K,RAMAKRISHNAN N,et al.Opportunities and challenges in association and episode discovery from electronic health records[J].IEEE Intelligent Systems,2011,26(5):83-87. [45]MAGBOO M S A,CORONEL A D.Data mining electronichealth records to support evidence-based clinical decisions[J/OL].Innovation in Medicine and Healthcare Systems,and Multimedia,2019:223-232.https://doi.org/10.1007/978-981-13-8566-722. [46]BRANTINGHAM P L.Computational criminology[C]//2011 European Intelligence and Security Informatics Conference.New York:IEEE Press,2011. [47]CHAPMAN P,CLINTON J,KERBER R,et al.CRISP-DM 1.0 step-by-step data mining guide[M].Chicago:SPSS Inc,1999. [48]GU J F,ZHU Z C.Knowing Wuli,sensing Shili,caring for Renli:methodology of the WSR approach[J].Systemic Practice and Action Research,2000,13(1):11-20. [49]GU J F,TANG X J,ZHU Z X.Review of Wuli-Shili-Renli system methodology[J].Journal of Transportation Systems Engineering and Information Technology,2007,7(6):51-60. [50]ZHU Z C.Enlightenment of international exchange on Wuli-Shili-Renli methodology[C]//Systems Engineering,Systems Science and Complexity Research Proceeding of 11th Annual Conference of Systems Engineering Society of China.Research Information Ltd.,2000:149-164. [51]GU J F,GAO F.Wuli-Shili-Renli system methodology based on the perspective of management science[J].Systems Engineering-Theory & Practice,1998,18(8):2-6. [52]KOU X D,GU J F.A twenty-five-year review of WSR metho-dology:origin,connotation,comparison and outlook[J].Ma-nagement Review,2021,33(5):3-14. [53]GU J F,TANG X J.From ancient system thoughts to modernoriental systems methodology[J].Systems Engineering-Theory &Practice,2000 20(1):90-93. [54]GU J F,TANG X J.Designing a water resources management decision support system:an application of the WSR approach[J].Systemic Practice and Action Research,2000,13(1):59-70. [55]SHE L Z.An empirical analysis of WSR system for large-scale engineering projects[J].China Civil Engineering Journal,2006,39(6):111-114. [56]ZHANG Q,XUE H F.An analytical model for environmental safety based on WSR methodology[J].China Soft Science,2010,25(1):165-174. [57]YE W,LIU X Y.Empirical study on factors affecting the system of science and technology innovation talent development under the perspective of WSR[J].Science and Technology Management Research,2017,37(9):36-43. [58]LI A H,XU W J,SHI Y.A New data fusion framework of business intelligence and analytics in economy,finance and management[C]//2020 IEEE/WIC/ACM International Joint Confe-rence on Web Intelligence and Intelligent Agent Technology(WI-IAT).New York:IEEE Press,2020:940-945. [59]PENG Y,KOU G.Research on theoretical framework of data mining based on domain knowledge[C]//The third(2008) Chinese Management Annual Conference-Information Management Conference Proceedings.Changsha:Chinese Research Council of Modern Management,2008:1242-1250. [60]MENG X F,DU Z J.Research on the big data fusion:issues and challenges[J].Journal of Computer Research and Development,2016,53(2):231-246. [61]JEVTIC P,REGIS L.A continuous-time stochastic model for the mortality surface of multiple populations[J/OL].Insurance:Mathematics and Economics,2019,88:181-195.https://doi.org/10.1016/j.insmatheco.2019.07.001. [62]MAO Y,GAN S.Economic evaluation model of freight distribution management in maritime port[J].Journal of Coastal Research,2019(Special Issue No.93):1059-1065. [63]ZUO A,ANN W S,ADAMOWICZ W L,et al.Measuring price elasticities of demand and supply of water entitlements based on stated and revealed preference data[J].American Journal of Agricultural Economics,2016,98(1):314-332. [64]LEE S I,YOO S J.Multimodal deep learning for finance:in-tegrating and forecasting international stock markets[J].The Journal of Supercomputing,2020,76(10):8294-8312. [65]WANG Q,XU W,HUANG X,et al.Enhancing intraday stock price manipulation detection by leveraging recurrent neural networks with ensemble learning[J].Neurocomputing,2019,347:46-58. [66]KONG D S.Research on technologies of stock market prediction based on quantity-price and sentiment analysis[D].Harbin:Harbin Institute of Technology,2019. [67]HOU J,HU N L,LI G Q,et al.Solution of operation and decision-making system oriented to mining group based on business intelligence[J].Computer Integrated Manufacturing Systems,2016,22(1):202-212. [68]CHEN G,YING Y H,WANG Y.Research on feature extraction of persons subject to enforcement for trust-breaking based on multivariate heterogeneous data fusion[J].Legality Vision,2020(32):187-188. [69]JI Z Y,PI H Y,YAO W N.A hybrid recommendation model based on fusion of multi-source heterogeneous data[J].Journal of Beijing University of Posts and Telecommunications,2019,42(1):126-132. [70]HUANG X B,ZHANG M X.Construction of enterprise competitor portrait based on multi-source data[J].Journal of Mo-dern Information,2020,40(11):13-21. [71]DING D.Research on the application of big data in hotel customer demand forecast under tourism background[J].Journal of Qiqihar University(Natural Science Edition),2020,36(6):90-94. |
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