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The proposed approach is compared with state-of-the-art process discovery algorithms on several synthetic and real-life event logs. The results show that compared to other algorithms, the proposed approach exhibits faster convergence and yields superior quality process models.<\/jats:p>","DOI":"10.3233\/aic-220219","type":"journal-article","created":{"date-parts":[[2024,4,2]],"date-time":"2024-04-02T17:56:40Z","timestamp":1712080600000},"page":"505-524","source":"Crossref","is-referenced-by-count":1,"title":["MantaRay-ProM: An efficient process model discovery algorithm"],"prefix":"10.1177","volume":"37","author":[{"given":"Shikha","family":"Gupta","sequence":"first","affiliation":[{"name":"Shaheed Sukhdev College of Business Studies, University of Delhi, New Delhi, India"}]},{"given":"Sonia","family":"Deshmukh","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Information Technology, KIET Institute of Technology, U.P., India"},{"name":"Department of Computer Science, University of Delhi, New Delhi, 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