Mining Survey Data

被引:0
|
作者
Lei, Hansheng [1 ]
Quweider, Mahmoud [1 ]
Zhang, Liyu [1 ]
Khan, Fitra [1 ]
机构
[1] Univ Texas Rio Grande Valley, Dept Comp Sci, Lab Data Intelligence & Secur, Brownsville, TX 78521 USA
关键词
survey data; mining survey data; dependent pattern; multiple regression; association rule;
D O I
10.1109/ICDIS.2019.00037
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Surveys are commonly used as an important data collection tool for empirical research in many applications such as social sciences, marketing and pedagogy. Survey data is becoming one of the major data sources in the era of big data. Conventional statistic tools are utilized to perform survey data analysis. Methods in data mining can extend the capabilities of statistics to explore and discover possible nuggets in massive data. While data mining on general databases has been intensive studied, very few has been done on survey data. Considering the specialities of survey data, this paper describes strategies in mining survey data using computational methods. A novel method for data preparation and dependent pattern mining is presented. Experiments on a real survey dataset were conducted to evaluate the strategies. Results on finding meaningful patterns are reported and discussed.
引用
收藏
页码:201 / 207
页数:7
相关论文
共 50 条
  • [31] A survey on mining multiple data sources
    Ramkumar, T.
    Hariharan, S.
    Selvamuthukumaran, S.
    WILEY INTERDISCIPLINARY REVIEWS-DATA MINING AND KNOWLEDGE DISCOVERY, 2013, 3 (01) : 1 - 11
  • [32] Brief survey of crowdsourcing for data mining
    Guo Xintong
    Wang Hongzhi
    Song, Yangqiu
    Hong, Gao
    EXPERT SYSTEMS WITH APPLICATIONS, 2014, 41 (17) : 7987 - 7994
  • [33] Data Mining for Internet of Things: A Survey
    Tsai, Chun-Wei
    Lai, Chin-Feng
    Chiang, Ming-Chao
    Yang, Laurence T.
    IEEE COMMUNICATIONS SURVEYS AND TUTORIALS, 2014, 16 (01): : 77 - 97
  • [34] Survey on privacy preserving data mining
    Wang P.
    International Journal of Digital Content Technology and its Applications, 2010, 4 (09) : 1 - 7
  • [35] A survey on federated learning in data mining
    Yu, Bin
    Mao, Wenjie
    Lv, Yihan
    Zhang, Chen
    Xie, Yu
    WILEY INTERDISCIPLINARY REVIEWS-DATA MINING AND KNOWLEDGE DISCOVERY, 2022, 12 (01)
  • [36] Classifier rules in data mining - A Survey
    Suganya, P.
    Sumathi, C. P.
    2014 IEEE INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND COMPUTING RESEARCH (IEEE ICCIC), 2014, : 671 - 673
  • [37] Data Mining Augmented Survey Research
    Hsu, Pei -Fang
    Chen, Shih-Chu
    He, Wen -Yang
    COMMUNICATIONS OF THE ASSOCIATION FOR INFORMATION SYSTEMS, 2024, 54
  • [38] Interestingness measures for data mining: A survey
    Geng, Liqiang
    Hamilton, Howard J.
    ACM COMPUTING SURVEYS, 2006, 38 (03) : 3
  • [39] Data Mining Techniques for IoT and Big Data -A Survey
    Shobanadevi, A.
    Maragatham, G.
    PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON INTELLIGENT SUSTAINABLE SYSTEMS (ICISS 2017), 2017, : 66 - 78
  • [40] Metaheuristics for data mining: survey and opportunities for big data
    Clarisse Dhaenens
    Laetitia Jourdan
    Annals of Operations Research, 2022, 314 : 117 - 140