{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T21:07:04Z","timestamp":1760044024327},"reference-count":0,"publisher":"IGI Global","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2015,1,1]]},"abstract":"<p>Software Performance is a critical aspect for all software products. In terms of Software Operation Knowledge, it concerns knowledge about the software product's performance when it is used by the end-users. In this paper the authors suggest data mining techniques that can be used to analyze software operation data in order to extract knowledge about the performance of a software product when it operates in the field. Focusing on Software-as-a-Service applications, the authors present the Performance Mining Method to guide the process of performance monitoring (in terms of device demands and responsiveness) and analysis (finding the causes of the identified performance anomalies). The method has been evaluated through a prototype which was implemented for an online financial management application in the Netherlands.<\/p>","DOI":"10.4018\/ijbir.2015010102","type":"journal-article","created":{"date-parts":[[2015,7,1]],"date-time":"2015-07-01T22:43:55Z","timestamp":1435790635000},"page":"11-29","source":"Crossref","is-referenced-by-count":1,"title":["The Performance Mining Method"],"prefix":"10.4018","volume":"6","author":[{"given":"Stella","family":"Pachidi","sequence":"first","affiliation":[{"name":"Department of Information and Computing Sciences, Utrecht University, Utrecht, Netherlands"}]},{"given":"Marco","family":"Spruit","sequence":"additional","affiliation":[{"name":"Department of Information and Computing Sciences, Utrecht University, Utrecht, Netherlands"}]}],"member":"2432","container-title":["International Journal of Business Intelligence Research"],"original-title":[],"language":"ng","link":[{"URL":"https:\/\/www.igi-global.com\/viewtitle.aspx?TitleId=132821","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,6,1]],"date-time":"2022-06-01T21:55:32Z","timestamp":1654120532000},"score":1,"resource":{"primary":{"URL":"https:\/\/services.igi-global.com\/resolvedoi\/resolve.aspx?doi=10.4018\/IJBIR.2015010102"}},"subtitle":["Extracting Performance Knowledge from Software Operation Data"],"short-title":[],"issued":{"date-parts":[[2015,1,1]]},"references-count":0,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2015,1]]}},"URL":"https:\/\/doi.org\/10.4018\/ijbir.2015010102","relation":{},"ISSN":["1947-3591","1947-3605"],"issn-type":[{"value":"1947-3591","type":"print"},{"value":"1947-3605","type":"electronic"}],"subject":[],"published":{"date-parts":[[2015,1,1]]}}}