计算机科学 ›› 2025, Vol. 52 ›› Issue (9): 195-211.doi: 10.11896/jsjkx.240800149
刘乐源1,2,3, 陈格格1, 吴炜5, 王永6, 周帆1,4
LIU Leyuan1,2,3, CHEN Gege1, WU Wei5, WANG Yong6, ZHOU Fan1,4
摘要： 近年来,各类信息系统和物联网不断发展,与人类日常生活的融合日趋紧密,由此产生的海量数据已经成为当今社会经济中的一种新型生产要素,甚至是国家战略资源。对数据要素进行有效的管理,越来越得到国家、企业和科研机构的重视。准确合理的数据分类分级作为数据治理任务中最基础的一步,将对后续数据的确权、共享、安全保护等产生重大影响。首先,对数据分类分级任务进行定义,并介绍了传统分类分级的方法;其次,对新近基于人工智能尤其是大语言模型的数据分类分级技术进行了概括和对比;随后,鉴于数据分类分级与行业的相关性,对重点行业和领域中的数据分类分级应用情况进行了介绍;最后,对数据分类分级技术的发展进行了前瞻,讨论了未来面临的新挑战和可能的发展方向。
中图分类号:
| [1]中华人民共和国国民经济和社会发展第十四个五年规划和2035年远景目标纲要[EB/OL].(2021-03-13)[2024-03-29].https://www.gov.cn/xinwen/2021-03/13/content_5592681.htm?eqid=9bb919dd00014d6d0000000364953b44. [2]国务院.国务院关于印发“十四五”数字经济发展规划的通知[EB/OL].(2021-12-12)[2024-03-29].https://www.gov.cn/zhengce/content/2022-01/12/content_5667817.htm. [3]十七部门关于印发《“数据要素×”三年行动计划(2024－2026年)》的通知[EB/OL].(2024-01-05)[2024-03-29].https://www.cac.gov.cn/2024-01/05/c_1706119078060945.htm. [4]中共中央国务院.关于构建更加完善的要素市场配置体制机制的意见[EB/OL].(2020-03-30)[2024-03-29].https://www.gov.cn/zhengce/2020-04/09/content_5500622.htm. [5]中共中央国务院.关于新时代加快完善社会主义市场经济体制的意见[EB/OL].(2020-05-11)[2024-03-29].https://www.gov.cn/zhengce/2020-05/18/content_5512696.html. [6]全国人民代表大会.中华人民共和国数据安全法[EB/OL].(2021-06-10)[2024-03-29].http://www.npc.gov.cn/npc/c2/c30834/202106/t20210610_311888.htm. [7]全国网络安全标准化技术委员会.GB/T 43697-2024《数据安全技术 数据分类分级规则》发布[EB/OL].(2024-03-21)[2024-03-29].https://www.tc260.org.cn/front/postDetail.html?id=20240321201412. [8]党和国家机构改革方案[J].机构与行政,2023(3):4-5. [9]MA F C,XIONG S Y,SUN Y J,et al.The Impact of Data Classification,Grading,and Right Confirmation on the Value Realization of Data Elements[J].Journal of Information Resources Management,2024,14(1):4-12. [10]CHEN B,LIN S Y.The Operational Logic and Practical Mechanism of Structurally Separated Data Property Rights:Aiming at Balancing Data Protection and Utilization[J].Nankai Journal(Philosophy and Social Sciences Edition),2024(1):36-50. [11]WANG Y,SU N.Key Issues and Practical Research on the Implementation of Government Data Classification and Grading in China[J].Big Data,2024,10(3):16-26. [12]LIU X M,LI C Z X,WU S C,et al.A Review of Text Classification Algorithms and Their Application Scenarios[J].Chinese Journal of Computers,2024,47(6):1244-1287. [13]AGGARWALC C.Data classification[M].Springer Interna-tional Publishing,2015. [14]KRISHNAIAH V,NARSIMHA G,CHANDRA N S.Survey of classification techniques in data mining[J].International Journal of Computer Sciences and Engineering,2014,2(9):65-74. [15]GABER MM,ZASLAVSKY A,KRISHNASWAMY S.A survey of classification methods in data streams[J].Data Streams:Models and Algorithms,2007,31:39-59. [16]LIAO F Y,HU L L,WANG J,et al.Research on Scientific Data Security Standards and Work Recommendations[J].Chinese Science Bulletin,2024(9):1142-1148. [17]WAN Y D,TAO C X.Practices and Insights on the Classification and Grading Management of U.S.Government Data[J].Journal of Information Theory and Practice,2020,43(12):172-177. [18]KATARAHWEIRE M,BAINOMUGISHA E,MUGHAL K A.Data classification for secure mobile health data collection systems[J].Development Engineering,2020,5:100054. [19]PENCINA M J,D’AGOSTINO SR R B,D’AGOSTINO JR R B,et al.Evaluating the added predictive ability of a new marker:from area under the ROC curve to reclassification and beyond[J].Statistics in Medicine,2008,27(2):157-172. [20]PAPINENI K,ROUKOS S,WARD T,et al.Bleu:a method for automatic evaluation of machine translation[C]//Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics.2002:311-318. [21]SUN X,LI X,LI J,et al.Text Classification via Large Language Models[C]//Findings of the Association for Computational Linguistics:EMNLP 2023.2023:8990-9005. [22]HARRISON J E,WEBER S,JAKOB R,et al.ICD-11:an international classification of diseases for the twenty-first century[J].BMC medical informatics and decision making,2021,21:1-10. [23]ABAYOMI-ALLI OO,DAMAŠEVIČIUS R,QAZI A,et al.Data augmentation and deep learning methods in sound classification:A systematic review[J].Electronics,2022,11(22):3795. [24]YANG L,TAO L,CHEN X,et al.Multi-scale semantic feature fusion and data augmentation for acoustic scene classification[J].Applied Acoustics,2020,163:107238. [25]PRASEETHA V M,JOBYP P.Speech emotion recognition using data augmentation[J].International Journal of Speech Technology,2022,25(4):783-792. [26]SUN S K,FAN J,SUN Z Q,et al.A Review of Image Data Augmentation Based on Deep Learning[J].Computer Science,2024,51(1):150-167. [27]YANG P B,SANG J T,ZHANG B,et al.A Review of Interpretability in Deep Models for Image Classification[J].Journal of Software,2023,34(1):230-254. [28]WU Y,LIU J.A Review of Black-Box Adversarial Attack Techniques for Image Analysis[J].Chinese Journal of Computers,2024(5):1138-1178. [29]YAN C,ZHANG S,LIU Y,et al.Feature prediction diffusionmodel for video anomaly detection[C]//Proceedings of the IEEE/CVF International Conference on Computer Vision.2023:5527-5537. [30]ZHU W,MA X,LIU Z,et al.Motionbert:A unified perspective on learning human motion representations[C]//Proceedings of the IEEE/CVF International Conference on Computer Vision.2023:15085-15099. [31]WANG J,CHEN G,HUANG Y,et al.Memory-and-anticipation transformer for online action understanding[C]//Proceedings of the IEEE/CVF International Conference on Computer Vision.2023:13824-13835. [32]LI X,HAN J,LEE J G,et al.Traffic density-based discovery of hot routes in road networks[C]//Advances in Spatial and Temporal Databases:10th International Symposium(SSTD 2007).Berlin:Springer,2007:441-459. [33]GURUNG S,LIN D,JIANG W,et al.Traffic information publication with privacy preservation[J].ACM Transactions on Intelligent Systems and Technology(TIST),2014,5(3):1-26. [34]MO Y,WU D,DU Y.Application of trajectory clustering and regionalization to ocean eddies in the south china sea[C]//2015 2nd IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services(ICSDM).IEEE,2015:45-48. [35]SUN L,LING X,HE K,et al.Community structure in trafficzones based on travel demand[J].Physica A:Statistical Mechanics and its Applications,2016,457:356-363. [36]KONG X,SONG X,XIA F,et al.LoTAD:Long-term traffic anomaly detection based on crowdsourced bus trajectory data[J].World Wide Web,2018,21:825-847. [37]MOHAMMADPOUR R A,ABEDI S M,BAGHERI S,et al.Fuzzy Rule-Based Classification System for Assessing Coronary Artery Disease[J].Computational and mathematical methods in medicine,2015,2015(1):564867. [38]CHEN P F,CHEN K C,LIAO W C,et al.Automatic International Classification of Diseases coding system:Deep contextualized language model with rule-based approaches[J].JMIR Medical Informatics,2022,10(6):e37557. [39]LEE J,YOON W,KIM S,et al.BioBERT:a pre-trained biomedical language representation model for biomedical text mining[J].Bioinformatics,2020,36(4):1234-1240. [40]VIOLOS J,TSERPES K,VARLAMIS I,et al.Text classifica-tion using the n-gram graph representation model over high frequency data streams[J].Frontiers in Applied Mathematics and Statistics,2018,4:41. [41]YU B,WANG Z H,SUN Y D,et al.Identification of Sensitive Data and Anomalous Behavior Analysis in Unstructured Documents[J].Journal of Intelligent Systems,2021,16(5):932-939. [42]SHI H,XU M.A data classification method using genetic algorithm and K-means algorithm with optimizing initial cluster center[C]//2018 IEEE International Conference on Computer and Communication Engineering Technology(CCET).IEEE,2018:224-228. [43]PENG J F,XV B M,ZHANG Y X,Research on key technologies for the security of railway sensitive data based on MLPS 2.0[J].Network Security Technology & Application,2021(1):138-142. [44]AMARAPPA S,SATHYANARAYANA S V.Data classification using Support vector Machine(SVM),a simplified approach[J].International Journal of Electronics & Computer Science Engineering,2014,3:435-445. [45]SHEYKHMOUSA M,MAHDIANPARI M,GHANBARI H,et al.Support vector machine versus random forest for remote sensing image classification:A meta-analysis and systematic review[J].IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,2020,13:6308-6325. [46]JOACHIMS T.Text categorization with support vector ma-chines:Learning with many relevant features[C]//European Conference on Machine Learning.Berlin:Springer,1998:137-142. [47]GUHATHAKURATA S,KUNDU S,CHAKRABORTY A,et al.A novel approach to predict COVID-19 using support vector machine[J].Data Science for COVID-19,2021,1:351-364. [48]HUANG H B.Research on Several Key Issues in Industrial Big Data Security Management[D].Beijing:Beijing University of Posts and Telecommunications,2023. [49]PERNKOPF F,PEHARZ R,TSCHIATSCHEK S.Introduction to probabilistic graphical models[M]//Academic Press Library in Signal Processing.Elsevier,2014:989-1064. [50]PASTORINO M,MOSER G,SERPICO S B,et al.Hierarchical probabilistic graphical models and deep convolutional neural networks for remote sensing image classification[C]//2021 29th European Signal Processing Conference(EUSIPCO).IEEE,2021:1740-1744. [51]KANG Z,YANG J.A probabilistic graphical model for the classification of mobile LiDAR point clouds[J].ISPRS Journal of Photogrammetry and Remote Sensing,2018,143:108-123. [52]GUO B,HUANG X,ZHANG F,et al.Classification of airborne laser scanning data using JointBoost[J].ISPRS Journal of Photogrammetry and Remote Sensing,2015,100:71-83. [53]XU S,FANG T,LI D,et al.Object classification of aerial images with bag-of-visual words[J].IEEE Geoscience and Remote Sensing Letters,2009,7(2):366-370. [54]COSTA V G,PEDREIRAC E.Recent advances in decisiontrees:An updated survey[J].Artificial Intelligence Review,2023,56(5):4765-4800. [55]QUINLAN J R.C4.5:programs for machine learning[M].Elsevier,2014. [56]HAMDI M,HILALI-JAGHDAM I,ELNAIM B E,et al.Forecasting and classification of new cases of COVID 19 before vaccination using decision trees and Gaussian mixture model[J].Alexandria Engineering Journal,2023,62:327-333. [57]ARIFUZZAMAN M,HASAN M R,TOMA T J,et al.An ad-vanced decision tree-based deep neural network in nonlinear data classification[J].Technologies,2023,11(1):24. [58]WANG Y X,ZHANG Y J.Nonnegative matrix factorization:A comprehensive review[J].IEEE Transactions on Knowledge and Data Engineering,2012,25(6):1336-1353. [59]LU G,LENG C,LI B,et al.Robust dual-graph discriminativeNMF for data classification[J].Knowledge-Based Systems,2023,268:110465. [60]CHEN M,HE Q.Quantitative Evaluation of Government Data Classification and Grading Policies Based on Feature Analysis[J].Information and Documentation Services,2024,45(1):78-88. [61]MINAEE S,KALCHBRENNER N,CAMBRIA E,et al.Deeplearning--based text classification:a comprehensive review[J].ACM Computing Surveys(CSUR),2021,54(3):1-40. [62]DONG L,SUO T,JIANG X.Network Application Classification with DNN Model[J].Journal of Physics:Conference Series.IOP Publishing,2020,1576(1):012026. [63]DENG Y,REN Z,KONG Y,et al.A hierarchical fusedfuzzy deep neural network for data classification[J].IEEE Transactions on Fuzzy Systems,2016,25(4):1006-1012. [64]PARTHASARATHY V,SARAVANAN S.Chaotic Sea Horse Optimization with Deep Learning Model for lung disease pneumonia detection and classification on chest X-ray images[J].Multimedia Tools and Applications,2024,83:69825-69847. [65]PEI L,JONES K A,SHBOULZ A,et al.Deep neural network analysis of pathology images with integrated molecular data for enhanced glioma classification and grading[J].Frontiers in Oncology,2021,11:668694. [66]LU H.City Data Classification and Grading Method Based on Deep Learning Clustering Algorithm[J].Industrial Technology Innovation,2021,8(4):73-78. [67]KRIZHEVSKY A,SUTSKEVER I,HINTONG E.Imagenetclassification with deep convolutional neural networks[J].Communication of the ACM,2017,60(6):84-90. [68]WEN X,WANG Z,CHEN Z,et al.Intelligent data directoryconstruction based on data classification and grading[C]//2023 International Conference on Distributed Computing and Electrical Circuits and Electronics(ICDCECE).IEEE,2023:1-8. [69]JI S,XU W,YANG M,et al.3D convolutional neural networks for human action recognition[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2012,35(1):221-231. [70]YU J,YANG B,WANG J,et al.2D CNN versus 3D CNN for false-positive reduction in lung cancer screening[J].Journal of Medical Imaging,2020,7(5):051202. [71]LAZEBNIK S,SCHMID C,PONCE J.Spatial pyramid matching[J/OL].http://slazebni.cs.illinois.edu/publications/pyramid_chapter.pdf. [72]SUN L,JIA K,YEUNG D Y,et al.Human action recognition using factorized spatio-temporal convolutional networks[C]//Proceedings of the IEEE International Conference on Computer Vision.2015:4597-4605. [73]WANG L,HUANG B,ZHAO Z,et al.Videomae v2:Scaling video masked autoencoders with dual masking[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition.2023:14549-14560. [74]DUTA I C,NGUYEN T A,AIZAWA K,et al.Boosting VLAD with double assignment using deep features for action recognition in videos[C]//2016 23rd International Conference on Pattern Recognition(ICPR).IEEE,2016:2210-2215. [75]MIRONICĂ I,DUŢĂ I C,IONESCUB,et al.A modified vector of locally aggregated descriptors approach for fast video classification[J].Multimedia Tools and Applications,2016,75:9045-9072. [76]LIU Y,JAIN A,ENG C,et al.A deep learning system for differential diagnosis of skin diseases[J].Nature Medicine,2020,26(6):900-908. [77]SCARSELLI F,GORI M,TSOI A C,et al.The graph neural network model[J].IEEE Transactions on Neural Networks,2008,20(1):61-80. [78]PENG H,LI J,HE Y,et al.Large-scale hierarchical text classification with recursively regularized deep graph-cnn[C]//Proceedings of the 2018 World Wide Web Conference.2018:1063-1072. [79]CHEN S S,WANG X D,LIU X Y.A Review of Breast Cancer Pathological Image Analysis Methods Based on Graph Neural Networks[J].Computer Science,2024,51(6):172-185. [80]PAN S J,YANG Q.A survey on transfer learning[J].IEEE Transactions on Knowledge and Data Engineering,2009,22(10):1345-1359. [81]LI J P,ZHU K Y,YANG S.Method for Recognizing Marine Fish in Complex Scenes Based on Transfer Learning[J].Computer Application and Software,2022,36(9):168-174. [82]HOWARD J,RUDER S.Universal Language Model Fine-tuningfor Text Classification[C]//Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics(Volume 1:Long Papers).2018:328-339. [83]GUPTA T,ZAKI M,KRISHNAN N M A,et al.MatSciBERT:A materials domain language model for text mining and information extraction[J].NPJ Computational Materials,2022,8(1):102. [84]KENTON J D M W C,TOUTANOVA LK.BERT:Pre-training of Deep Bidirectional Transformers for Language Understanding[C]//Proceedings of NAACL-HLT.2019:4171-4186. [85]HUANG A H,WANG H,YANG Y.FinBERT:A large language model for extracting information from financial text[J].Contemporary Accounting Research,2023,40(2):806-841. [86]ARSLAN Y,ALLIX K,VEIBER L,et al.A comparison of pre-trained language models for multi-class text classification in the financial domain[C]//Companion Proceedings of the Web Conference 2021.2021:260-268. [87]MENG Y,ZHANG Y,HUANG J,et al.Text Classification Using Label Names Only:A Language Model Self-Training Approach[C]//Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing(EMNLP).2020:9006-9017. [88]KANT N,PURI R,YAKOVENKO N,et al.Practical text classification with large pre-trained language models[J].arXiv:1812.01207,2018. [89]KRAUSE B,LU L,MURRAY I,et al.Multiplicative LSTM for sequence modelling[J].arXiv:1609.07959,2016. [90]SARZYNSKA-WAWER J,WAWER A,PAWLAK A,et al.Detecting formal thought disorder by deep contextualized word representations[J].Psychiatry Research,2021,304:114135. [91]WAHBA Y,MADHAVJI N,STEINBACHER J.A comparisonof svm against pre-trained language models(plms) for text classification tasks[C]//International Conference on Machine Learning,Optimization,and Data Science.Cham:Springer Nature Switzerland,2022:304-313. [92]TERECHSHENKO Z,LINDER F,PADMAKUMAR V,et al.A Comparison of Methods in Political Science Text Classification:Transfer Learning Language Models for Politics[J].Social Science Electronic Publishing[2025-05-27].DOI:10.2139/ssrn.3724644. [93]LEWIS M,LIU Y,GOYAL N,et al.BART:Denoising Se-quence-to-Sequence Pre-training for Natural Language Generation,Translation,and Comprehension[C]//Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics.2020:7871-7880. [94]BROWN T,MANN B,RYDER N,et al.Language models arefew-shot learners[J].Advances in Neural Information Proces-sing Systems,2020,33:1877-1901. [95]CHAE Y,DAVIDSON T.Large language models for text classification:From zero-shot learning to fine-tuning[J/OL].https://scispace.com/pdf/large-language-models-for-text-classification-from-zero-shot-20cnjjxzcm.pdf. [96]DING B,QIN C,LIU L,et al.Is GPT-3 a Good Data Annotator?[C]//The 61st Annual Meeting of the Association For Computational Linguistics.2023. [97]GILARDI F,ALIZADEH M,KUBLI M.ChatGPT outperforms crowd workers for text-annotation tasks[J].Proceedings of the National Academy of Sciences,2023,120(30):e2305016120. [98]YU D,LI L,SU H,et al.Assessing the potential of LLM-assisted annotation for corpus-based pragmatics and discourse analysis:The case of apology[J].International Journal of Corpus Linguistics,2024,29(4):534-561. [99]CHEN J,CHEN P,WU X.Generating Chinese Event Extraction Method Based on ChatGPT and Prompt Learning[J].Applied Sciences,2023,13(17):9500. [100]FREI J,KRAMER F.Annotated dataset creation through large language models for non-english medical NLP[J].Journal of Biomedical Informatics,2023,145:104478. [101]DAGDELEN J,DUNN A,LEE S,et al.Structured information extraction from scientific text with large language models[J].Nature Communications,2024,15(1):1418. [102]JULIANTO I T,KURNIADI D,SEPTIANA Y,et al.Alternative text pre-processing using chat GPT open AI[J].Jurnal Nasional Pendidikan Teknik Informatika:JANAPATI,2023,12(1):67-77. [103]LYNCH R M.RapidMiner:Data mining use cases and business analytics applications[M].CRC Press,2016. [104]ZHU M,STANIVUK S,PETROVIC A,et al.IncorporatingLLM Priors into Tabular Learners[C]//NeurIPS 2023 Second Table Representation Learning Workshop.2023. [105]PURI R,CATANZARO B.Zero-shot text classification withgenerative language models[J].arXiv:1912.10165,2019. [106]RAFFEL C,SHAZEER N,ROBERTS A,et al.Exploring the limits of transfer learning with a unified text-to-text transformer[J].Journal of machine learning research,2020,21(140):1-67. [107]YANG Z.XLNet:Generalized Autoregressive Pretraining forLanguage Understanding[J].arXiv:1906.08237,2019. [108]WU F,SOUZA A,ZHANG T,et al.Simplifying graph convolutional networks[C]//International Conference on Machine Learning.PMLR,2019:6861-6871. [109]LIN Y,MENG Y,SUN X,et al.Bertgcn:Transductive text clas-sification by combining gcn and bert[J].arXiv:2105.05727,2021. [110]IONESCU R T,BUTNARUA M.Vector of locally-aggregated word embeddings(VLAWE):A novel document-level representation[J].arXiv:1902.08850,2019. [111]HAN T,LIU C,YANG W,et al.Deep transfer network with joint distribution adaptation:A new intelligent fault diagnosis framework for industry application[J].ISA Transactions,2020,97:269-281. [112]YUAN Y,WEI J,HUANG H,et al.Review of resampling techniques for the treatment of imbalanced industrial data classification in equipment condition monitoring[J].Engineering Applications of Artificial Intelligence,2023,126:106911. [113]GLAESER A,SELVARAJ V,LEE S,et al.Applications of deep learning for fault detection in industrial cold forging[J].International Journal of Production Research,2021,59(16):4826-4835. [114]SOUZA R M,NASCIMENTO E G S,MIRANDA U A,et al.Deep learning for diagnosis and classification of faults in industrial rotating machinery[J].Computers & Industrial Enginee-ring,2021,153:107060. [115]ZHANG K.Research on the Classification and Grading Scheme of Telecommunication Big Data[J].China Strategic Emerging Industries,2023(32):53-55. [116]IRARRÁZAVAL M E,MALDONADO S,PÉREZ J,et al.Telecom traffic pumping analytics via explainable data science[J].Decision Support Systems,2021,150:113559. [117]ARIK S Ö,PFISTER T.Tabnet:Attentive interpretable tabular learning[C]//Proceedings of the AAAI Conference on Artificial Intelligence.2021:6679-6687. [118]TOU X D,ZHAO Z Y.On the Construction of Energy DataClassification and Grading System in the Evolution of Ecological Civilization[J].Journal of Nanjing University(Philosophy,Humanities,and Social Sciences),2024,61(1):41-49,162-163. [119]PAPADOPOULOS S,KONTOKOSTA C E.Grading buildings on energy performance using city benchmarking data[J].Applied Energy,2019,233:244-253. [120]CHEN T,GUESTRIN C.Xgboost:A scalable tree boosting system[C]//Proceedings of the 22nd ACM Sigkdd International Conference on Knowledge Discovery and Data Mining.2016:785-794. [121]ZHANG J,TU Y,LIU J,et al.Regional public transportation safety risk grading assessment under time dimension:A case study of Chinese mainland[J].Transport Policy,2022,126:343-354. [122]LIU L,ZHI Y.Research on the Classification and Grading Management Route of Public Security Traffic Management Data[J].Road Traffic Management,2023(5):40-43. [123]BAI Z X,WANG T,GUO M D,et al.Research on Classification and Grading Methods for Transportation Administrative Data[J].Information Security Research,2023,9(8):808-813. [124]RAO W,LI B Q,REN C Y,et al.Research on Classification and Grading Protection Paths for Railway Data[J].Railway Communication Signal,2023,59(11):49-54. [125]CHEN Y R,HONG X,ZHANG H B,et al.Research on Data Classification and Protection Strategies in the Field of Railway Transportation Dispatching[J].Railway Transportation and Economy,2024,46(2):134-141. [126]WANG J Y,ZHANG S B,YE R Z,et al.Research on Automatic Data Classification Methods for the Transportation Industry Based on Deep Learning[J].Applied Science and Technology,2024,51(2):145-150. [127]ZHANG X Y,DAI Y C.Classification,Grading,and Security Protection Technologies for Hydraulic Data[J].Yangtze River,2023,54(S2):232-237. [128]HOU H,FU Q,ZHANG Y.An Empirical Study on the Classification,Grading,Sharing and Opening of Healthcare Big Data Based on Current Policies and Standards[C]//2021 3rd International Conference on Intelligent Medicine and Image Processing.2021:116-121. [129]ZHANG S F,MA Y H,ZHANG J C,et al.Research on Classification Guidelines for Health and Medical Scientific Data Based on Data Security[J].Journal of Medical Informatics,2023,44(8):19-24. [130]LI B B.Research on Medical Data Security Risk AssessmentMethods Based on Probabilistic Hesitant Fuzzy Sets[D].Zhengzhou:North China University of Water Resources and Electric Power,2023. [131]CRUZ-ROA A A,AREVALO OVALLE J E,MADABHUSHI A,et al.A deep learning architecture for image representation,visual interpretability and automated basal-cell carcinoma cancer detection[C]//Medical Image Computing and Computer-Assisted Intervention-MICCAI 2013:16th International Conference,Nagoya,Japan,Part II 16.Berlin:Springer,2013:403-410. [132]WU Z,SHI G,CHEN Y,et al.Coarse-to-fine classification for diabetic retinopathy grading using convolutional neural network[J].Artificial Intelligence in Medicine,2020,108:101936. [133]SIVAPRASAD S,OYETUNDE S.Impact of injection therapy on retinal patients with diabetic macular edema or retinal vein occlusion[J].Clinical Ophthalmology,2016,10:939-946. [134]MA J L.Research on Classification and Grading of Educational Data Based on the Data Security Law[J].Journal of Tianjin University of Technology and Education,2023,27(1):55-60. [135]RODRÍGUEZ P,VILLANUEVA A,DOMBROVSKAIA L,et al.A methodology to design,develop,and evaluate machine learning models for predicting dropout in school systems:the case of Chile[J].Education and Information Technologies,2023,28(8):10103-10149. [136]VITAL T P R,SANGEETA K,KUMAR K K.Student classification based on cognitive abilities and predicting learning performances using machine learning models[J].International Journal of Computing and Digital Systems,2021,10(1):63-75. [137]VO C,NGUYEN H P.An enhanced CNN model on temporaleducational data for program-level student classification[C]//Asian Conference on Intelligent Information and Database Systems.Cham:Springer International Publishing,2020:442-454. [138]国务院办公厅.科学数据管理办法[EB/OL].(2018-03-17)[2024-03-28].https://www.gov.cn/zhengce/content/2018-04/02/content_5279272.htm. [139]LU P,LIU R F,LI Z X,et al.Discussion on the Classification and Grading of Seismic Scientific Data[J].Northwest Seismological Journal,2007,29(3):248-251,255. [140]ALMASAN P,SUÁREZ-VARELA J,RUSEKK,et al.Deep reinforcement learning meets graph neural networks:Exploring a routing optimization use case[J].Computer Communications,2022,196:184-194. [141]MAHMUD M,KAISER M S,HUSSAIN A,et al.Applications of deep learning and reinforcement learning to biological data[J].IEEE Transactions on Neural Networks and Learning Systems,2018,29(6):2063-2079. |
|
||
首页