{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,19]],"date-time":"2025-11-19T18:25:16Z","timestamp":1763576716577,"version":"3.45.0"},"publisher-location":"Gdansk, Poland; Belgrade, Serbia","reference-count":23,"publisher":"University of Gdansk, Department of Business Informatics & University of Belgrade, Faculty of Organizational Sciences","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"DOI":"10.62036\/isd.2025.52","type":"proceedings-article","created":{"date-parts":[[2025,11,19]],"date-time":"2025-11-19T00:45:28Z","timestamp":1763513128000},"source":"Crossref","is-referenced-by-count":0,"title":["Filling the Gap in Time: Intelligent Imputation of Historical Parish Records"],"prefix":"10.62036","author":[{"given":"Adam","family":"Kiersztyn","sequence":"first","affiliation":[{"name":"Lublin University of Technology, Poland"}]},{"given":"Piotr","family":"Rachwal","sequence":"additional","affiliation":[{"name":"The John Paul II Catholic University of Lublin, Poland"}]},{"given":"Krystyna","family":"Kiersztyn","sequence":"additional","affiliation":[{"name":"Lublin University of Technology, Poland"}]}],"member":"48375","published-online":{"date-parts":[[2025,11,17]]},"reference":[{"key":"ref0","unstructured":"[1] Chojecki, D.: Od spo\u0142eczenstwa tradycyjnego do nowoczesnego. Demografia i zdrowot-' nos'c g\u0142\u00f3wnych o' srodk\u00f3w miejskich Pomorza Zachodniego w dobie przyspieszonej in-' dustrializacji i urbanizacji w Niemczech (1871-1913). Szczecin: Wydawnictwo Naukowe Uniwersytetu Szczecinskiego, 2014.'"},{"key":"ref1","unstructured":"[2] Gesundheitsamt, D. R.: Ver\u00f6ffentlichungen des Kaiserlichen Gesundheitsamts. Berlin: Verlag von Julius Springer, 1918."},{"key":"ref2","doi-asserted-by":"publisher","unstructured":"[3] Jerez, J. M., Molina, I., Garc\u00eda-Laencina, P. J., Alba, E., Ribelles, N., Mart\u00edn, M., and Franco, L.: Missing data imputation using statistical and machine learning methods in a real breast cancer problem. In: Artificial intelligence in medicine 50.2 (2010), pp. 105- 115.","DOI":"10.1016\/j.artmed.2010.05.002"},{"key":"ref3","doi-asserted-by":"publisher","unstructured":"https:\/\/doi.org\/10.1016\/j.artmed.2010.05.002","DOI":"10.1016\/j.artmed.2010.05.002"},{"key":"ref4","doi-asserted-by":"publisher","unstructured":"[4] Karczmarek, P., Kiersztyn, A., Pedrycz, W., and Al, E.: K-means-based isolation forest. In: Knowledge-based systems 195 (2020), p. 105659.","DOI":"10.1016\/j.knosys.2020.105659"},{"key":"ref5","doi-asserted-by":"publisher","unstructured":"https:\/\/doi.org\/10.1016\/j.knosys.2020.105659","DOI":"10.1016\/j.knosys.2020.105659"},{"key":"ref6","doi-asserted-by":"publisher","unstructured":"[5] Karczmarek, P., Kiersztyn, A., Pedrycz, W., Badurowicz, M., Czerwinski, D., and Mon-' tusiewicz, J.: K-medoids clustering and fuzzy sets for isolation forest. In: 2021 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE. 2021, pp. 1-8.","DOI":"10.1109\/FUZZ45933.2021.9494460"},{"key":"ref7","doi-asserted-by":"publisher","unstructured":"https:\/\/doi.org\/10.1109\/FUZZ45933.2021.9494460","DOI":"10.1109\/FUZZ45933.2021.9494460"},{"key":"ref8","doi-asserted-by":"publisher","unstructured":"[6] Karczmarek, P., Kiersztyn, A., Pedrycz, W., and Czerwinski, D.: Fuzzy c-means-based' isolation forest. In: Applied Soft Computing 106 (2021), p. 107354.","DOI":"10.1016\/j.asoc.2021.107354"},{"key":"ref9","doi-asserted-by":"publisher","unstructured":"https:\/\/doi.org\/10.1016\/j.asoc.2021.107354","DOI":"10.1016\/j.asoc.2021.107354"},{"key":"ref10","doi-asserted-by":"publisher","unstructured":"[7] Kiersztyn, A., Czerwinski, D., Czerma' nski, E., Oniszczuk-Jastrza\u02dbbek, A., Smoli' nski, K.,' Miazek, P., Laskowicz, T., Jankiewicz, J., Rzepka, A., and Miskiewicz, R.: Data integrity' analysis on the example of AIS database. In: Scientific Papers of Silesian University of Technology. Organization & Management\/Zeszyty Naukowe Politechniki Slaskiej. Seria Organizacji i Zarzadzanie 208 (2024).","DOI":"10.29119\/1641-3466.2024.208.9"},{"key":"ref11","doi-asserted-by":"publisher","unstructured":"https:\/\/doi.org\/10.29119\/1641-3466.2024.208.9","DOI":"10.29119\/1641-3466.2024.208.9"},{"key":"ref12","doi-asserted-by":"publisher","unstructured":"[8] Kiersztyn, A., Karczmarek, P., Kiersztyn, K., and Pedrycz, W.: Detection and classification of anomalies in large datasets on the basis of information granules. In: IEEE Transactions on Fuzzy Systems 30.8 (2021), pp. 2850-2860.","DOI":"10.1109\/TFUZZ.2021.3076265"},{"key":"ref13","doi-asserted-by":"publisher","unstructured":"https:\/\/doi.org\/10.1109\/TFUZZ.2021.3076265","DOI":"10.1109\/TFUZZ.2021.3076265"},{"key":"ref14","doi-asserted-by":"publisher","unstructured":"[9] Kiersztyn, A., Karczmarek, P., \u0141opucki, R., Pedrycz, W., Al, E., Kitowski, I., and Zbyryt, A.: Data imputation in related time series using fuzzy set-based techniques. In: 2020 IEEE international conference on fuzzy systems (FUZZ-IEEE). IEEE. 2020, pp. 1-8.","DOI":"10.1109\/FUZZ48607.2020.9177617"},{"key":"ref15","doi-asserted-by":"publisher","unstructured":"https:\/\/doi.org\/10.1109\/FUZZ48607.2020.9177617","DOI":"10.1109\/FUZZ48607.2020.9177617"},{"key":"ref16","doi-asserted-by":"publisher","unstructured":"[10] Little, R. J. and Rubin, D. B.: Statistical analysis with missing data. John Wiley & Sons, 2019.","DOI":"10.1002\/9781119482260"},{"key":"ref17","doi-asserted-by":"publisher","unstructured":"https:\/\/doi.org\/10.1002\/9781119482260","DOI":"10.1002\/9781119482260"},{"key":"ref18","doi-asserted-by":"publisher","unstructured":"[11] Pedrycz, W.: Fuzzy sets in pattern recognition: methodology and methods. In: Pattern recognition 23.1-2 (1990), pp. 121-146.","DOI":"10.1016\/0031-3203(90)90054-O"},{"key":"ref19","doi-asserted-by":"publisher","unstructured":"https:\/\/doi.org\/10.1016\/0031-3203(90)90054-O","DOI":"10.1016\/0031-3203(90)90054-O"},{"key":"ref20","doi-asserted-by":"publisher","unstructured":"[12] Rubin, D. B.: Multiple imputation for survey nonresponse. 1987.","DOI":"10.1002\/9780470316696"},{"key":"ref21","doi-asserted-by":"publisher","unstructured":"https:\/\/doi.org\/10.1002\/9780470316696","DOI":"10.1002\/9780470316696"},{"key":"ref22","unstructured":"[13] Yoon, J., Jordon, J., and Schaar, M.: Gain: Missing data imputation using generative adversarial nets. In: International conference on machine learning. PMLR. 2018, pp. 5689- 5698."}],"event":{"name":"33rd International Conference on Information Systems Development","start":{"date-parts":[[2025,9,3]]},"location":"Belgrade, Serbia","end":{"date-parts":[[2025,9,5]]},"acronym":"ISD 2025"},"container-title":["International Conference on Information Systems Development","Proceedings of the 33rd International Conference on Information Systems Development"],"original-title":[],"link":[{"URL":"https:\/\/aisel.aisnet.org\/cgi\/viewcontent.cgi?article=1731&context=isd2014&unstamped=1","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,19]],"date-time":"2025-11-19T18:13:44Z","timestamp":1763576024000},"score":1,"resource":{"primary":{"URL":"https:\/\/aisel.aisnet.org\/isd2014\/proceedings2025\/datascience\/22"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,17]]},"references-count":23,"URL":"https:\/\/doi.org\/10.62036\/isd.2025.52","relation":{},"ISSN":["2938-5202"],"issn-type":[{"type":"print","value":"2938-5202"}],"subject":[],"published":{"date-parts":[[2025,11,17]]}}}