2011/06/25 by Oleg Chertov, Оleg Chertov, Chertov, Oleg +2
Computer Science · Physics and Astronomy · #Data Management and Algorithms #Data Mining Algorithms and Applications #Databases (cs.DB) #FOS: Computer and information sciences #FOS: Physical sciences #Physics and Society (physics.soc-ph) #Social and Information Networks (cs.SI) #Time Series Analysis and Forecasting #cs.DB #cs.SI #physics.soc-ph
paper · pdf · doi:10.48550/arxiv.1106.5122
World Conference on Soft Computing WConSC-2011 (San Francisco State University, California, USA), 8 pages, 6 figures
arxiv created 2011/06/25 · openalex publication_date 2011/06/25 · arxiv updated 2011/06/28 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Not long ago primary census data became available to publicity. It opened qualitatively new perspectives not only for researchers in demography and sociology, but also for those people, who somehow face processes occurring in society. In this paper authors propose using Data Mining methods for searching hidden patterns in census data. A novel clustering-based technique is described as well. It allows determining factors which influence people behavior, in particular decision-making process (as an example, a decision whether to have a baby or not). Proposed technique is based on clustering a set of respondents, for whom a certain event have already happened (for instance, a baby was born), and discovering clusters' prototypes from a set of respondents, for whom this event hasn't occurred yet. By means of analyzing clusters' and their prototypes' characteristics it is possible to identify which factors influence the decision-making process. Authors also provide an experimental example of the described approach usage.