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Fraud detection on event logs of goods and services procurement business process using Heuristics Miner algorithm

机译:欺诈检测商品和服务采购业务流程的事件日志采用启发式矿工算法

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Event logs are history records that contain sequence data for the activity of a case that has been executed by an information system. Event logs can be valuable information with a technique called mining process. With this technique, cheating on the business processes of an enterprise can be detected early on. Thus, the company can commit further examination of business processes, especially the business process of procurement of goods and services to achieve business process is expected.[8] In this study, management data of event log obtained from log data at each event transaction procurement and services. The event log data is then analyzed using a heuristic miner algorithm. Heuristics miner algorithm chosen because it has advantages that are not owned by Alpha++ algorithm that this algorithm can calculate the frequency relation between activities in the log to determine the causal dependency. Heuristic Miner can be used to determine the predominant process of thousands of logs and detect behaviors that are not common in a process.[11] This study aims to detect anomalies on business processes that occur during the process of procurement of goods and services by calculating the fitness value of the event log into the system. Heuristic miner algorithm using the results obtained identification accuracy of 0.88%.
机译:事件日志是包含由信息系统执行的案例的活动的序列数据的历史记录。事件日志可以是具有称为挖掘过程的技术的有价值的信息。通过这种技术,可以提前检测到企业的业务流程作弊。因此,该公司可以进一步审查业务流程,特别是预期商业流程的商业流程,预计会有业务流程。[8]在本研究中,从每个事件交易采购和服务的日志数据获得的事件日志管理数据。然后使用启发式矿工算法分析事件日志数据。启发式矿工算法选择,因为它具有不受Alpha ++算法所拥有的优势,即该算法可以计算日志中活动之间的频率关系来确定因果关系。启发式矿工可用于确定数千个日志的主要过程,并检测过程中不常见的行为。[11]本研究旨在通过计算事件登录到系统的适应性值来检测商业和服务过程中发生的业务流程的异常。启发式矿工算法使用结果获得的鉴定精度为0.88%。

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