{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,7,13]],"date-time":"2022-07-13T07:40:11Z","timestamp":1657698011737},"reference-count":19,"publisher":"Tsinghua University Press","issue":"3","license":[{"start":{"date-parts":[[2019,9,2]],"date-time":"2019-09-02T00:00:00Z","timestamp":1567382400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJCS"],"published-print":{"date-parts":[[2019,9,2]]},"abstract":"<jats:sec><jats:title content-type=\"abstract-subheading\">Purpose<\/jats:title><jats:p>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 data set 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 data set are designed by combining expert knowledges and simple statistics. By utilizing the emerging data mining algorithms, we proposed a comprehensive data management and data mining approach for GSS data sets.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title><jats:p>The approach are designed to be operated in a two-phase manner: a data management phase which can improve the quality of GSS data by performing attribute pre-processing and filter-based attribute selection; a data mining phase which can extract hidden knowledge from the data set by performing data mining analysis including prediction analysis, classification analysis, association analysis and clustering analysis.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Findings<\/jats:title><jats:p>According to experimental evaluation results, the paper have the following findings: Performing attribute selection on GSS data set can increase the performance of both classification analysis and clustering analysis; all the data mining analysis can effectively extract hidden knowledge from the GSS data set; the knowledge generated by different data mining analysis can somehow cross-validate each other.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title><jats:p>By leveraging the power of data mining techniques, the proposed approach can explore knowledge in a fine-grained manner with minimum human interference. Experiments on Chinese General Social Survey data set are conducted at the end to evaluate the performance of our approach.<\/jats:p><\/jats:sec>","DOI":"10.1108\/ijcs-09-2019-0023","type":"journal-article","created":{"date-parts":[[2019,12,9]],"date-time":"2019-12-09T15:24:40Z","timestamp":1575905080000},"page":"315-332","source":"Crossref","is-referenced-by-count":0,"title":["Knowledge discovery in sociological databases"],"prefix":"10.26599","volume":"3","author":[{"given":"Zhiwen","family":"Pan","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiangtian","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yiqiang","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jesus","family":"Pacheco","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lianjun","family":"Dai","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jun","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"11138","reference":[{"key":"ref10","first-page":"619","article-title":"Secondary data analysis: a method of which the time has come","volume":"3","author":"johnston","year":"2017","journal-title":"QQML2010 Qualitative and Quantitative Methods in Libraries"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2261-9-9"},{"key":"ref12","first-page":"9","author":"lorenzo","year":"2013","journal-title":"Individual Income Tax Law Chinese Tax Law and International Treaties"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/34.990133"},{"key":"ref14","year":"2019","journal-title":"Chinese General Society Survey 2019"},{"key":"ref15","year":"2017","journal-title":"Age Categories Life Cycle Groupings"},{"key":"ref16","first-page":"86","article-title":"The problems in rural English teaching and the optimization path: a study based on the Chinese general social survey data","volume":"6","author":"tan","year":"2014","journal-title":"Asian Agricultural Research"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1111\/j.2517-6161.1996.tb02080.x"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.2753\/CSA2162-0555460301"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1145\/1273496.1273641"},{"key":"ref4","article-title":"Classification performance of rank aggregation techniques for ensemble gene selection","author":"dittman","year":"0","journal-title":"The Twenty-Sixth International FLAIRS Conference"},{"key":"ref3","author":"davis","year":"1991","journal-title":"The NORC General Social Survey A User's Guide"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1145\/371920.372165"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1080\/17525098.2010.492636"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1155\/2017\/2460174"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1214\/07-AOAS148"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1145\/1133905.1133907"},{"key":"ref1","year":"2014","journal-title":"1200 0 55 006 &#x2013; age standard"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1111\/jssr.12168"}],"container-title":["International Journal of Crowd Science"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.emerald.com\/insight\/content\/doi\/10.1108\/IJCS-09-2019-0023\/full\/xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.emerald.com\/insight\/content\/doi\/10.1108\/IJCS-09-2019-0023\/full\/html","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,7,12]],"date-time":"2022-07-12T14:09:07Z","timestamp":1657634947000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.emerald.com\/insight\/content\/doi\/10.1108\/IJCS-09-2019-0023\/full\/html"}},"subtitle":["An application on general society survey dataset"],"short-title":[],"issued":{"date-parts":[[2019,9,2]]},"references-count":19,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2019,9,2]]}},"alternative-id":["10.1108\/IJCS-09-2019-0023"],"URL":"https:\/\/doi.org\/10.1108\/ijcs-09-2019-0023","relation":{},"ISSN":["2398-7294","2398-7294"],"issn-type":[{"value":"2398-7294","type":"print"},{"value":"2398-7294","type":"print"}],"subject":[],"published":{"date-parts":[[2019,9,2]]}}}