Comprehensive data management and analytics for general society survey dataset

Zhiwen Pan, Shuangye Zhao, Jesus Pacheco, Yuxin Zhang, Xiaofan Song, Yiqiang Chen, Lianjun Dai, Jun Zhang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The General Society Survey(GSS) is a kind of government-funded survey which aims at examining the Socio-economic status, quality of life, and structure of contemporary society. GSS dataset is regarded as one of the authoritative source for the government and organization practitioners to make data-driven policies. The previous analytic approaches for GSS dataset are designed by combining expert knowledges and simple statistics. In this paper, we proposed a comprehensive data management and data mining approach for GSS datasets. The approach is designed to be operated in a two-phase manner: a data management phase which can improve the quality of GSS data by performing attribute preprocessing and filter-based attribute selection; a data mining phase which can extract hidden knowledges from the dataset by performing data mining analysis including prediction analysis, classification analysis, association analysis and clustering analysis. By leveraging the power of data mining techniques, our proposed approach can explore knowledges in a fine-grained manner with minimum human interference. Experiments on Chinese General Social Survey dataset are conducted at the end to evaluate the performance of our approach.

Original languageEnglish
Title of host publicationProceedings of the 4th International Conference on Crowd Science and Engineering, ICCSE 2019
PublisherAssociation for Computing Machinery
Pages195-203
Number of pages9
ISBN (Electronic)9781450376402
DOIs
StatePublished - 18 Oct 2019
Event4th International Conference on Crowd Science and Engineering, ICCSE 2019 - Jinan, China
Duration: 18 Oct 201921 Oct 2019

Publication series

NameACM International Conference Proceeding Series

Conference

Conference4th International Conference on Crowd Science and Engineering, ICCSE 2019
Country/TerritoryChina
CityJinan
Period18/10/1921/10/19

Bibliographical note

Publisher Copyright:
© 2019 Association for Computing Machinery.

Keywords

  • Data management
  • Data mining
  • Decision support systems
  • Knowledge discovery
  • Society survey

Fingerprint

Dive into the research topics of 'Comprehensive data management and analytics for general society survey dataset'. Together they form a unique fingerprint.

Cite this