使用顺序和声明模式探索业务流程偏差(CS)
业务流程偏差指的是一个业务流程执行的子集以消极或积极的方式偏离预期或理想结果的现象。业务流程的异常执行包括那些违反遵从性规则的执行,或者低于或超过性能目标的执行。异常挖掘是通过分析支持业务流程执行的系统存储的事件日志来发现异常执行的原因。在本文中,首先通过使用基于顺序模式和声明模式以及它们的组合的特性来研究解释业务流程中的偏差的问题。然后,通过基于纯数据属性值和数据感知声明规则的特性,利用事件的数据属性和事件日志中的跟踪,进一步改进解释。然后通过直接和间接的方法提取出表征偏差的解释,进行规则归纳。利用多个域的真实记录,一系列的功能类型和不同形式的决策规则评估的能力,准确区分non-deviant和不正常的执行的过程以及最终结果返回给用户的可理解性。
原文题目:Exploring Business Process Deviance with Sequential and Declarative Patterns
原文:Business process deviance refers to the phenomenon whereby a subset of the executions of a business process deviate, in a negative or positive way, with respect to {their} expected or desirable outcomes. Deviant executions of a business process include those that violate compliance rules, or executions that undershoot or exceed performance targets. Deviance mining is concerned with uncovering the reasons for deviant executions by analyzing event logs stored by the systems supporting the execution of a business process. In this paper, the problem of explaining deviations in business processes is first investigated by using features based on sequential and declarative patterns, and a combination of them. Then, the explanations are further improved by leveraging the data attributes of events and traces in event logs through features based on pure data attribute values and data-aware declarative rules. The explanations characterizing the deviances are then extracted by direct and indirect methods for rule induction. Using real-life logs from multiple domains, a range of feature types and different forms of decision rules are evaluated in terms of their ability to accurately discriminate between non-deviant and deviant executions of a process as well as in terms of understandability of the final outcome returned to the users.
相关文章
- 日志到底应该怎么打印?
- 前后端接口鉴权全解Cookie/Session/Token的区别
- 四种 Python 连接 MySQL 数据库的方法
- 前端基础知识整理汇总一
- Python 操作 MySQL 数据库的三个模块
- TinyDB 一个纯Python编写的轻量级数据库
- 一张五亿数据量的表执行不了,开发和DBA差点大打出手……
- 太全了!用Python操作MySQL的使用教程集锦!
- 实现动态展示多算法,这个Python库助你发现网络图社区结构
- 相同执行计划,为何有执行快慢的差别
- 如何使用Python算法进行交易
- 5G变1G,线上日志瘦身还有这些骚操作
- 巧用ActionFilterAttribute实现API日志的记录
- 聊一聊函数之美
- 提升编码水平,这本Python软件工程开源书籍为研究人员量身打造
- 使用Func<T, TResult> 委托实现API日志的记录
- React中的任务饥饿行为
- 如何在Python中操作MySQL?
- 一篇长文帮你彻底搞懂React的调度机制原理
- JDK15类的后半生:准备、解析、初始化、卸载过程详解