{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,10]],"date-time":"2025-06-10T17:30:06Z","timestamp":1749576606856,"version":"3.37.3"},"reference-count":0,"publisher":"IOS Press","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2012]]},"abstract":"<jats:p>This paper presents investigating the customercharacteristics from the bad debt list ofa mail order corporation. So far, suchinvestigations have not made intensively, especiallyprivate defaultrisks and conventional method for predicting such risks depend on the employee&amp;apos;s working experiences. For these reason, at first,we observedtheactual bad debt list from amail order corporationand analyzedsales data. From the results of the observation, we makeuse of the machine learningmethod to characterizethe potential bad debt customers. Intensive research hasrevealed that the characteristicsof customers, who might fall into the bad debt list, popularitems and so on. This method willmake use forthe revenue expansion;improvement of collectionof the bad debts.<\/jats:p>","DOI":"10.3233\/978-1-61499-105-2-867","type":"book-chapter","created":{"date-parts":[[2025,2,20]],"date-time":"2025-02-20T12:06:08Z","timestamp":1740053168000},"source":"Crossref","is-referenced-by-count":1,"title":["Building Knowledge for Characterization of the Bad Debt Customers in the Mail Order Industry with Random Forest"],"prefix":"10.3233","author":[{"family":"Takahashi Masakazu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"family":"Azuma Hiroki","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"family":"Ikeda Masanori","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"family":"Tsuda Kazuhiko","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","Advances in Knowledge-Based and Intelligent Information and Engineering Systems"],"original-title":[],"deposited":{"date-parts":[[2025,2,20]],"date-time":"2025-02-20T13:00:16Z","timestamp":1740056416000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.medra.org\/servlet\/aliasResolver?alias=iospressISSNISBN&issn=0922-6389&volume=243&spage=867"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2012]]},"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/978-1-61499-105-2-867","relation":{},"ISSN":["0922-6389"],"issn-type":[{"value":"0922-6389","type":"print"}],"subject":[],"published":{"date-parts":[[2012]]}}}