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The infrequent behavior or noise has a negative influence on the process discovery procedure. This article presents a technique to remove infrequent behavior from event logs by calculating the minimum expectation of the process event log. The method was evaluated in detail, and the results showed that its application in existing process discovery algorithms significantly improves the quality of the discovered process models and that it scales well to large datasets.<\/jats:p>","DOI":"10.4018\/ijcini.2020040101","type":"journal-article","created":{"date-parts":[[2020,2,28]],"date-time":"2020-02-28T12:51:44Z","timestamp":1582894304000},"page":"1-15","source":"Crossref","is-referenced-by-count":8,"title":["Filtering Infrequent Behavior in Business Process Discovery by Using the Minimum Expectation"],"prefix":"10.4018","volume":"14","author":[{"given":"Ying","family":"Huang","sequence":"first","affiliation":[{"name":"Gannan Normal University, Ganzhou, China"}]},{"given":"Liyun","family":"Zhong","sequence":"additional","affiliation":[{"name":"Gannan Normal University, Ganzhou, China"}]},{"given":"Yan","family":"Chen","sequence":"additional","affiliation":[{"name":"South China Agricultural University, Guangzhou, China"}]}],"member":"2432","reference":[{"key":"IJCINI.2020040101-0","first-page":"237","article-title":"Outlier analysis","author":"C. 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