Please wait a minute...
Data Analysis and Knowledge Discovery  2019, Vol. 3 Issue (3): 25-35    DOI: 10.11925/infotech.2096-3467.2018.0784
Current Issue | Archive | Adv Search |
A Survey of User Profiles Methods
Guangshang Gao()
Business School, Guilin University of Technology, Guilin 541004, China
Download: PDF (523 KB)   HTML ( 25
Export: BibTeX | EndNote (RIS)      

[Objective] This paper discusses the mechanism of User Profiles construction process from the perspectives of design thinking and data types. [Coverage] We used Google Scholar and CNKI to search literatures with the keywords “User Personas” and “User Profiles”. Then we selected 90 representative literatures on User Personas in conjunction with topic screening, intensive reading and retrospective method. [Methods] Firstly, this paper studies the construction process of User Profiles from the perspective of design thinking, specifically combining the four perspectives of Goal-Directed, Role-Based, Engagement-Based and Fiction-Based. Second, it analyzes construction process of User Profiles from the perspective of data types, specifically combining Ontology or Concept, Subject or Topic, Interest or Preference, Behavior or Log, Multidimension or Fusion. Next, the construction methods are compared in detail from three aspects: logical ideas, performance characteristics and limitations. Finally, the next step for research on User Profiles is prospected. [Results] User Profiles technology plays a vital role in many areas such as online public opinion governance, advertising marketing and personalized services. [Limitations] There is no in-depth analysis of the evaluation indicators of User Profiles algorithms. [Conclusions] Although the existing methods of User Profiles can meet the needs of many applications to a certain extent, in the era of big data, it still faces the challenges of data sparsity, scene intelligence perception and user interest migration.

Key wordsUser Profiles      Ontology      Topic      Interest      Behavior Log     
Received: 18 July 2018      Published: 17 April 2019

Cite this article:

Guangshang Gao. A Survey of User Profiles Methods. Data Analysis and Knowledge Discovery, 2019, 3(3): 25-35.

URL:     OR

[1] Cooper A.The Inmates are Running the Asylum: Why High-Tech Products Drive Us Crazy and How to Restore the Sanity[M]. Sams Publishing, 2004.
[2] Pruitt J, Adlin T.The Persona Lifecycle: Keeping People in Mind Throughout Product Design[M]. Morgan Kaufmann Publishers Inc., 2010.
[3] Nielsen L.Personas - User Focused Design[M]. London: Springer, 2013.
[4] Lerouge C, Ma J, Sneha S, et al.User Profiles and Personas in the Design and Development of Consumer Health Technologies[J]. International Journal of Medical Informatics, 2013, 82(11): e251-e268.
[5] Brickey J, Walczak S, Burgess T.Comparing Semi- Automated Clustering Methods for Persona Development[J]. IEEE Transactions on Software Engineering, 2012, 38(3): 537-546.
[6] Mianowska B, Nguyen N T.Tuning User Profiles Based on Analyzing Dynamic Preference in Document Retrieval Systems[J]. Multimedia Tools and Applications, 2013, 65(1): 93-118.
[7] Nielsen L.Personas in a More User-Focused World[A]// Nielsen L. Personas-User Focused Design[M]. Springer, 2013: 129-154.
[8] Salminen J, Jung S G, An J, et al.Findings of a User Study of Automatically Generated Personas[C]// Proceeding of the 2018 CHI Conference on Human Factors in Computing Systems. ACM, 2018: 1-6.
[9] Chen R, Liu J.Personas: Powerful Tool for Designers[A]// Luchs M G, Swan K S, Griffin A. Design Thinking: New Product Development Essentials from the PDMA[M]. Wiley, 2016: 27-40.
[10] Cooper A, Reimann R, Cronin D, et al.About Face: The Essentials of Interaction Design[M]. The 4th Edition. Wiley, 2014.
[11] Grudin J, Pruitt J.Personas, Participatory Design and Product Development: An Infrastructure for Engagement[C]// Proceedings of the 2002 Participatory Design Conference. 2002: 144-161.
[12] Sønderstrup-Andersen E.Personas: En Domæneanalytisk Tilgang[J]. Dansk Biblioteksforskning, 2007, 3(2): 61-75.
[13] Nielsen L.Introduction: Stories About Users[A]// Personas-User Focused Design[M]. Springer, 2013.
[14] Nielsen L. Engaging Personas and Narrative Scenarios[OL]. [2018-03-22].
[15] Floyd I R, Jones M C, Twidale M B.Resolving Incommensurable Debates: A Preliminary Identification of Persona Kinds, Attributes, and Characteristics[J]. Artifact, 2008, 2(1): 12-26.
[16] Norman D.Ad-hoc Personas & Empathetic Focus[A]// The Persona Lifecycle: Keeping People in Mind During Product Design[M]. Morgan Kaufmann Publishers Inc., 2006: 154-157.
[17] Djajadiningrat J P, Gaver W W, Fres J.Interaction Relabelling and Extreme Characters: Methods for Exploring Aesthetic Interactions[C]// Proceedings of the 3rd Conference on Designing Interactive Systems: Processes, Practices, Methods, and Techniques. ACM, 2000: 66-71.
[18] Blythe M A, Wright P C.Pastiche Scenarios: Fiction as a Resource for User Centred Design[J]. Interacting with Computers, 2006, 18(5): 1139-1164.
[19] Liu W, Jin F, Zhang X.Ontology-Based User Modeling for E-Commerce System[C]// Proceedings of the 3rd International Conference on Pervasive Computing and Applications. IEEE, 2008: 260-263.
[20] Middleton S E, Shadbolt N R, De Roure D C. Ontological User Profiling in Recommender Systems[J]. ACM Transactions on Information Systems(TOIS), 2004, 22(1): 54-88.
[21] Edwards N.E-commerce Website Personalisation Based on Ontological Profiling[D]. Wales: Cardiff University, 2015.
[22] Golemati M, Katifori A, Vassilakis C, et al.Creating an Ontology for the User Profile: Method and Applications[C]// Proceedings of the 1st International Conference on Research Challenges in Information Science. 2007: 407-412.
[23] Jayanthi J, Jayakumar K S, Surendran S.Generation of Ontology Based User Profiles for Personalized Web Search[C]// Proceedings of the 3rd International Conference on Electronics Computer Technology. 2011: 240-244.
[24] Calegari S, Pasi G.Personal Ontologies: Generation of User Profiles Based on the YAGO Ontology[J]. Information Processing & Management, 2013, 49(3): 640-658.
[25] Skillen K L, Chen L, Nugent C D, et al.Ontological User Profile Modeling for Context-Aware Application Personalization[C]// Proceedings of the 2012 International Conference on Ubiquitous Computing and Ambient Intelligence. 2012: 261-268.
[26] 单晓红, 张晓月, 刘晓燕. 基于在线评论的用户画像研究——以携程酒店为例[J]. 情报理论与实践, 2018, 41(4): 1-10.
[26] (Shan Xiaohong, Zhang Xiaoyue, Liu Xiaoyan.Research on User Portrait Based on Online Review: Taking Ctrip Hotel as an Example[J]. Information Studies: Theory & Application, 2018, 41(4): 1-10.)
[27] 郑建兴, 张博锋, 岳晓冬, 等. 基于友邻-用户模型的微博主题推荐研究[J]. 山东大学学报: 理学版, 2013, 48(11): 59-65.
[27] (Zheng Jianxing, Zhang Bofeng, Yue Xiaodong, et al.Research on Themes Recommendation in Micro-Blogging Scenario Based on Neighbor-User Profile[J]. Journal of Shangdong University: Natural Science, 2013, 48(11): 59-65.)
[28] 牛温佳, 刘吉强, 石川. 用户网络行为画像:大数据中的用户网络行为画像分析与内容推荐应用[M]. 北京: 电子工业出版社, 2016.
[28] (Niu Wenjia, Liu Jiqiang, Shi Chuan.User Network Behavior Portrait: The Analysis of Users’ Network Behaviors and the Application of Content Recommendation in Big Data[M]. Beijing: Electronic Industry Press, 2016.)
[29] Leung K W T, Lee D L. Deriving Concept-Based User Profiles from Search Engine Logs[J]. IEEE Transactions on Knowledge and Data Engineering, 2010, 22(7): 969-982.
[30] Sasikala P, Vidhya V.An Efficient Concept-based Mining Model for Deriving User Profiles[J]. International Journal of Applied Information Systems, 2014, 1(6): 26-34.
[31] Bloedorn E, Mani I, Macmillan T R.Machine Learning of User Profiles: Representational Issues[OL]. arXiv Preprint, arXiv: 9712002.
[32] Trajkova J, Gauch S.Improving Ontology-Based User Profiles[C]// Proceedings of the RIAO’04 Coupling Approaches, Coupling Media and Coupling Languages for Information Retrieval. 2004: 380-390.
[33] Pazzani M, Billsus D.Learning and Revising User Profiles: The Identification of Interesting Web Sites[J]. Machine Learning, 1997, 27(3): 313-331.
[34] Rish I.An Empirical Study of the Naive Bayes Classifier[C]// Proceedings of the 2001 IJCAI Workshop on Empirical Methods in Artificial Intelligence. 2001: 41-46.
[35] Miller G A.WordNet: A Lexical Database for English[J]. Communications of the ACM, 1995, 38(11): 39-41.
[36] Domingos P, Pazzani M.On the Optimality of the Simple Bayesian Classifier Under Zero-One Loss[J]. Machine Learning, 1997, 29(2-3): 103-130.
[37] Billsus D, Pazzani M J.User Modeling for Adaptive News Access[J]. User Modeling and User-Adapted Interaction, 2000, 10(2-3): 147-180.
[38] Blei D M, Ng A Y, Jordan M I.Latent Dirichlet Allocation[J]. Journal of Machine Learning Research, 2003, 3: 993-1022.
[39] Tang J, Yao L, Zhang D, et al. A Combination Approach to Web User Profiling[J]. ACM Transactions on Knowledge Discovery from Data(TKDD), 2010, 5(1): Article No.2.
[40] Kim J Y, Collins-Thompson K, Bennett P N, et al.Characterizing Web Content, User Interests, and Search Behavior by Reading Level and Topic[C]// Proceedings of the 5th ACM International Conference on Web Search and Data Mining. ACM, 2012: 213-222.
[41] Veningston K, Shanmugalakshmi R.Combining User Interested Topic and Document Topic for Personalized Information Retrieval[C]// Proceedings of the 2014 International Conference on Big Data Analytics. Springer, 2014: 60-79.
[42] 林燕霞, 谢湘生. 基于社会认同理论的微博群体用户画像[J]. 情报理论与实践, 2018, 41(3): 142-148.
[42] (Lin Yanxia, Xie Xiangsheng.User Portrait of Diversified Groups in Micro-blog Based on Social Identity Theory[J]. Information Studies: Theory & Application, 2018, 41(3): 142-148.)
[43] Chen Z.Modeling Research on Micro-blog Users[C]// Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering. 2013.
[44] 曾鸿, 吴苏倪. 基于微博的大数据用户画像与精准营销[J]. 现代经济信息, 2016(16): 306-308.
[44] (Zeng Hong, Wu Suni.User Image and Precision Marketing on Account of Big Data in Weibo[J]. Modern Economic Information, 2016(16): 306-308.)
[45] 李文峰. 基于主题模型的用户建模研究[D]. 北京: 北京邮电大学, 2013.
[45] (Li Wenfeng.Topic Model Based User Modeling[D]. Beijing: Beijing University of Posts and Telecommunications, 2013.)
[46] 郭光明. 基于社交大数据的用户信用画像方法研究[D]. 合肥: 中国科学技术大学, 2017.
[46] (Guo Guangming.User Credit Profiling Techniques for Online Users with Big Social Data[D]. Hefei: University of Science and Technology of China, 2017.)
[47] Pazzani M J, Billsus D.Content-Based Recommendation Systems[A]// Brusilovsky P, Kobsa A, Nejdl W. The Adaptive Web[M]. Springer, 2007: 325-341.
[48] Carmagnola F, Cena F, Gena C.User Modeling in the Social Web[C]// Proceedings of the 2007 International Conference on Knowledge-Based and Intelligent Information and Engineering Systems. Springer, 2007: 745-752.
[49] Li X, Guo L, Zhao Y E.Tag-Based Social Interest Discovery[C]// Proceedings of the 17th International Conference on World Wide Web. ACM, 2008: 675-684.
[50] Agrawal R, Srikant R.Fast Algorithms for Mining Association Rules[C]// Proceedings of the 20th International Conference on Very Large Data Bases. 1994: 487-499.
[51] 张小可, 沈文明, 杜翠凤. 贝叶斯网络在用户画像构建中的研究[J]. 移动通信, 2016, 40(22): 22-26.
[51] (Zhang Xiaoke, Shen Wenming, Du Cuifeng.Research on Bayesian Network in User Portrait Construction[J]. Mobile Communications, 2016, 40(22): 22-26.)
[52] Wu L, Ge Y, Liu Q, et al.Modeling Users’ Preferences and Social Links in Social Networking Services: A Joint-Evolving Perspective[C]// Proceedings of the 30th AAAI Conference on Artificial Intelligence. 2016: 279-286.
[53] Wang W, Zhao D, Luo H, et al.Mining User Interests in Web Logs of an Online News Service Based on Memory Model[C]// Proceedings of the IEEE 8th International Conference on Networking, Architecture and Storage. 2013: 151-155.
[54] Li J, Zuo X Q, Zhou M Q, et al.Mining Explainable User Interests from Scalable User Behavior Data[J]. Procedia Computer Science, 2013, 17: 789-796.
[55] Hoang T A.Modeling User Interest and Community Interest in Microbloggings: An Integrated Approach[C]// Proceedings of the 2015 Pacific-Asia Conference on Knowledge Discovery and Data Mining. Springer, 2015: 708-721.
[56] Sugiyama K, Hatano K, Yoshikawa M.Adaptive Web Search Based on User Profile Constructed Without Any Effort from Users[C]// Proceedings of the 13th International Conference on World Wide Web. ACM, 2004: 675-684.
[57] Agichtein E, Brill E, Dumais S, et al.Learning User Interaction Models for Predicting Web Search Result Preferences[C]// Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval. ACM, 2006: 3-10.
[58] Filipova B T, Martinovska C.Analysing Customer Profiles Using Data Mining Techniques[C]// Proceedings of the 34th International Conference on Information Technology Interfaces. 2012: 73-78.
[59] Fawcett T, Provost F.Combining Data Mining and Machine Learning for Effective Fraud Detection[C]// Proceedings of the 2nd International Conference on Knowledge Discovery and Data Mining. 1996: 14-19.
[60] Rafter R, Smyth B.Passive Profiling from Server Logs in an Online Recruitment Environment[C]// Proceedings of the 17th International Joint Conference on Artificial Intelligence. 2001.
[61] Adomavicius G, Tuzhilin A.User Profiling in Personalization Applications Through Rule Discovery and Validation[C]// Proceedings of the 5th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM, 1999: 377-381.
[62] Witten I H, Frank E, Hall M A.Data Mining: Practical Machine Learning Tools and Techniques[M]. United State: Morgan Kauffman, 2011.
[63] Adomavicius G, Tuzhilin A.Using Data Mining Methods to Build Customer Profiles[J]. Computer, 2001, 34(2): 74-82.
[64] Moudani W, Zaarour G, Mora-Camino F.Fuzzy Classification of Customer Insolvency in Mobile Telecommunication[J]. International Journal of Decision Support System Technology, 2014, 6(3): 1-29.
[65] Nawaz W, Khan K U, Lee Y K.A Multi-User Perspective for Personalized Email Communities[J]. Expert Systems with Applications, 2016, 54: 265-283.
[66] 张慷. 手机用户画像在大数据平台的实现方案[J]. 信息通信, 2014(2): 266-267.
[66] (Zhang Kang.Implementation Scheme of Mobile User Portrait in Big Data Platform[J]. Information & Communications, 2014(2): 266-267.)
[67] 汪强兵, 章成志. 融合内容与用户手势行为的用户画像构建系统设计与实现[J]. 数据分析与知识发现, 2017, 1(2): 80-86.
[67] (Wang Qiangbing, Zhang Chengzhi.Constructing Users Profiles with Content and Gesture Behaviors[J]. Data Analysis and Knowledge Discovery, 2017, 1(2): 80-86.)
[68] Wang G, Zhang X, Tang S, et al.Unsupervised Clickstream Clustering for User Behavior Analysis[C]// Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems. ACM, 2016: 225-236.
[69] Wang G, Zhang X, Tang S, et al.Clickstream User Behavior Models[J]. ACM Transactions on the Web(TWEB), 2017, 11(4): 1-37.
[70] Zhang X, Brown H F, Shankar A.Data-driven Personas: Constructing Archetypal Users with Clickstreams and User Telemetry[C]// Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems. ACM, 2016: 5350-5359.
[71] Nasraoui O, Soliman M, Saka E, et al.A Web Usage Mining Framework for Mining Evolving User Profiles in Dynamic Web Sites[J]. IEEE Transactions on Knowledge and Data Engineering, 2008, 20(2): 202-215.
[72] Iglesias J A, Angelov P, Ledezma A, et al.Creating Evolving User Behavior Profiles Automatically[J]. IEEE Transactions on Knowledge and Data Engineering, 2012, 24(5): 854-867.
[73] Ma H, Cao H, Yang Q, et al.A Habit Mining Approach for Discovering Similar Mobile Users[C]// Proceedings of the 21st International Conference on World Wide Web. 2012: 231-240.
[74] Chen X, Pang J, Xue R. Constructing and Comparing User Mobility Profiles[J]. ACM Transactions on the Web (TWEB), 2014, 8(4): Article No.21.
[75] Zhu H, Chen E, Xiong H, et al.Mining Mobile User Preferences for Personalized Context-Aware Recommendation[J]. ACM Transactions on Intelligent Systems & Technology, 2014, 5(4): 1-27.
[76] Wang H, Zhai C, Liang F, et al.User Modeling in Search Logs via a Nonparametric Bayesian Approach[C]// Proceedings of the 7th ACM International Conference on Web Search and Data Mining. ACM, 2014: 203-212.
[77] 段建勇, 魏晓亮, 张梅, 等. 基于网络日志的用户兴趣模型构建[J]. 情报科学, 2013, 31(9): 78-82.
[77] (Duan Jianyong, Wei Xiaoliang, Zhang Mei, et al.Web Query Log Based User Interest Model[J]. Information Science, 2013, 31(9): 78-82.)
[78] 黄文彬, 徐山川, 吴家辉, 等. 移动用户画像构建研究[J]. 现代情报, 2016, 36(10): 54-61.
[78] (Huang Wenbin, Xu Shanchuan, Wu Jiahui, et al.The Profile Construction of the Mobile User[J]. Journal of Modern Information, 2016, 36(10): 54-61.)
[79] Rosenthal S, Mckeown K.Age Prediction in Blogs: A Study of Style, Content, and Online Behavior in Pre- and Post-Social Media Generations[C]// Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics. 2011: 763-772.
[80] Mueller J, Stumme G.Gender Inference Using Statistical Name Characteristics in Twitter[C]// Proceedings of the the 3rd Multidisciplinary International Social Networks Conference on Social Informatics. ACM, 2016: 1-8.
[81] Marquardt J, Farnadi G, Vasudevan G, et al.Age and Gender Identification in Social Media[C]// Proceedings of CLEF 2014 Evaluation Labs. 2014: 1129-1136.
[82] An J, Kwak H, Jansen B J.Automatic Generation of Personas Using YouTube Social Media Data[C]// Proceedings of the 50th International Conference on System Sciences. 2017.
[83] Jung S G, An J, Kwak H, et al.Persona Generation from Aggregated Social Media Data[C]// Proceedings of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems. ACM, 2017: 1748-1755.
[84] 王凌霄, 沈卓, 李艳. 社会化问答社区用户画像构建[J]. 情报理论与实践, 2018, 41(1): 129-134.
[84] (Wang Lingxiao, Shen Zhuo, Li Yan.User Profiling of Socail Q&A Community[J]. Information Studies: Theory & Application, 2018, 41(1): 129-134.)
[85] 费鹏, 林鸿飞, 杨亮, 等. 一种用于构建用户画像的多视角融合框架[J]. 计算机科学, 2018, 45(1): 179-182, 204.
[85] (Fei Peng, Lin Hongfei, Yang Liang, et al.Multi-view Ensemble Framework for Constructing User Profile[J]. Computer Science, 2018, 45(1): 179-182, 204.)
[86] 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. ACM, 2016: 785-794.
[87] 李恒超, 林鸿飞, 杨亮, 等. 一种用于构建用户画像的二级融合算法框架[J]. 计算机科学, 2018, 45(1): 157-161.
[87] (Li Hengchao, Lin Hongfei, Yang Liang, et al.Two-level Stacking Algorithm Framework for Building User Portrait[J]. Computer Science, 2018, 45(1): 157-161.)
[88] 李琳, 刘锦行, 孟祥福, 等. 融合评分矩阵与评论文本的商品推荐模型[J]. 计算机学报, 2018, 41(7): 1559-1573.
[88] (Li Lin, Liu Jinhang, Meng Xiangfu, et al.Recommendation Models by Exploiting Rating Matrix and Review Text[J]. Chinese Journal of Computers, 2018, 41(7): 1559-1573.)
[89] 叶舒雁, 张未展, 齐天亮, 等. 一种基于传感器与用户行为数据分析的移动学习场景感知分类方法[J]. 计算机研究与发展, 2016, 53(12): 2721-2728.
[89] (Ye Shuyan, Zhang Weizhan, Qi Tianliang, et al.A Sensor and User Behavior Data Analysis Based Method of Mobile Learning Situation Perception[J]. Journal of Computer Research and Development, 2016, 53(12): 2721-2728.)
[90] 尚燕敏, 曹亚男, 韩毅, 等. 基于主题和大众影响的用户动态行为倾向预测[J]. 计算机学报, 2018, 41(7): 1434-1447.
[90] (Shang Yanmin, Cao Ya’nan, Han Yi, et al.Recommending the Right Items for User Temporal Interest with Matrix Factorization Through Topic Model[J]. Chinese Journal of Computers, 2018, 41(7): 1434-1447.)
[1] Ma Yingxue,Zhao Jichang. Patterns and Evolution of Public Opinion on Weibo During Natural Disasters: Case Study of Typhoons and Rainstorms[J]. 数据分析与知识发现, 2021, 5(6): 66-79.
[2] Wu Xu,Chen Chunxu. Detecting Topics of Group Chats with Multiple Strategies[J]. 数据分析与知识发现, 2021, 5(5): 1-9.
[3] Song Ruoxuan,Qian Li,Du Yu. Identifying Academic Creative Concept Topics Based on Future Work of Scientific Papers[J]. 数据分析与知识发现, 2021, 5(5): 10-20.
[4] Yi Huifang,Liu Xiwen. Analyzing Patent Technology Topics with IPC Context-Enhanced Context-LDA Model[J]. 数据分析与知识发现, 2021, 5(4): 25-36.
[5] Li Yueyan,Wang Hao,Deng Sanhong,Wang Wei. Research Trends of Information Retrieval——Case Study of SIGIR Conference Papers[J]. 数据分析与知识发现, 2021, 5(4): 13-24.
[6] Wang Hongbin,Wang Jianxiong,Zhang Yafei,Yang Heng. Topic Recognition of News Reports with Imbalanced Contents[J]. 数据分析与知识发现, 2021, 5(3): 109-120.
[7] Shen Si,Li Qinyu,Ye Yuan,Sun Hao,Ye Wenhao. Topic Mining and Evolution Analysis of Medical Sci-Tech Reports with TWE Model[J]. 数据分析与知识发现, 2021, 5(3): 35-44.
[8] Zhang Xin,Wen Yi,Xu Haiyun. A Prediction Model with Network Representation Learning and Topic Model for Author Collaboration[J]. 数据分析与知识发现, 2021, 5(3): 88-100.
[9] Zhao Tianzi, Duan Liang, Yue Kun, Qiao Shaojie, Ma Zijuan. Generating News Clues with Biterm Topic Model[J]. 数据分析与知识发现, 2021, 5(2): 1-13.
[10] Zhang Jinzhu, Yu Wenqian. Topic Recognition and Key-Phrase Extraction with Phrase Representation Learning[J]. 数据分析与知识发现, 2021, 5(2): 50-60.
[11] Ding Hao, Ai Wenhua, Hu Guangwei, Li Shuqing, Suo Wei. A Personalized Recommendation Model with Time Series Fluctuation of User Interest[J]. 数据分析与知识发现, 2021, 5(11): 45-58.
[12] Sheng Shu, Huang Qi, Yang Yang, Xie Qiwen, Qin Xinguo. Exchanging Chinese Medical Information Based on HL7 FHIR[J]. 数据分析与知识发现, 2021, 5(11): 13-28.
[13] Wang Wei, Gao Ning, Xu Yuting, Wang Hongwei. Topic Evolution of Online Reviews for Crowdfunding Campaigns[J]. 数据分析与知识发现, 2021, 5(10): 103-123.
[14] Chen Hao, Zhang Mengyi, Cheng Xiufeng. Identifying Cross-Region Patent Collaboration Opportunities Using LDA and Decision Trees——Case Study of Universities from Guangdong and Wuhan[J]. 数据分析与知识发现, 2021, 5(10): 37-50.
[15] Zeng Zhen,Li Gang,Mao Jin,Chen Jinghao. Data Governance and Domain Ontology of Regional Public Security[J]. 数据分析与知识发现, 2020, 4(9): 41-55.
  Copyright © 2016 Data Analysis and Knowledge Discovery   Tel/Fax:(010)82626611-6626,82624938