Time Prediction Based on Process Mining Taking Concept Drift into Consideration

Autor:	Zhao Li, Fan Fang Huang, Li Qun Zhang
Rok vydání:	2014
Předmět:	Process modeling Concept drift Computer science business.industry Event (computing) General Engineering Process mining Cluster (spacecraft) computer.software_genre Machine learning Order (exchange) Data mining Artificial intelligence business computer
Zdroj:	Advanced Materials Research. :2101-2105
ISSN:	1662-8985
Popis:	Process mining allows for the automated discovery of process models from event logs. These models provide insights and enable various types of model-based analysis. Now many scholars have made a great contribution on predicting the completion time of running instances and a lot of algorithms have been proposed, but they mostly ignored concept drift which means the influence of the external factors. In order to improve the accuracy of the prediction, we take the concept drift into account. We do cluster analysis on the annotated transition system. Experiments show that our algorithm has a considerable degree of improvement over the previous.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::fefe3e778ccd47f9888196ae5293a892 https://doi.org/10.4028/www.scientific.net/amr.989-994.2101 Zobrazit plný text záznamu