Document Type

Article

Abstract

Business processes can be automatic, semiautomatic or manual processes. Semi-automatic and manual processes are involved in some parts by people. Understanding how people work or make judgments in processes can help management to evaluate their performance and suggest essential information to enhance their decision making. This paper describes a case study of using process mining to discover decision patterns of a worker in a semi-automatic business process. It was found that the discovered rules could be improved by enhancing the business execution log file with semantic related data. The experimental results before and after improvements were compared.

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