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

机译:使用启发式Miner算法对商品和服务采购业务流程的事件日志进行欺诈检测

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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:事件日志是历史记录,其中包含由信息系统执行的案件活动的顺序数据。使用称为“挖掘过程”的技术,事件日志可以成为有价值的信息。使用此技术,可以及早发现对企业业务流程的作弊行为。因此,公司可以对业务流程进行进一步的检查,尤其是期望实现商品和服务采购的业务流程。[8]在本研究中,事件日志的管理数据是从每个事件事务采购和服务处的日志数据中获取的。然后使用启发式挖掘器算法分析事件日志数据。选择启发式矿工算法是因为它具有Alpha ++算法不具备的优势,该算法可以计算日志中活动之间的频率关系以确定因果关系。启发式Miner可用于确定成千上万条日志的主要流程,并检测流程中不常见的行为。[11]本研究旨在通过计算事件日志进入系统的适用性值,来检测在商品和服务采购过程中发生的业务流程异常。使用启发式矿工算法的结果获得的识别精度为0.88%。

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