PROVED: A Tool for Graph Representation and Analysis of Uncertain Event Data

不确定事件的时态逻辑及其在PROLOG扩展中的实现

A Temporal Logic for Uncertain Events and An Outline of A Possible Implementation in An Extension of PROLOG

现实生活中许多事件的发生都存在不确定性。在本文中，我们开发了一个时间逻辑来处理这种不确定的事件，并概述了一个可能的实现扩展的PROTEGO。事件表示为模糊集的隶属函数给出的事件在给定的时间间隔内发生的可能性。所开发的时态逻辑简单但功能强大。它可以有效地确定不确定事件或其组合之间的各种时间关系。PROTECH提供了一个统一的基底，在其上有效地实现这样一个不确定事件的时态逻辑

Probabilistic and Non-Deterministic Event Data in Process Mining: Embedding Uncertainty in Process Analysis Techniques

Process mining is a subfield of process science that analyzes event data collected in databases called event logs. Recently, novel types of event data have become of interest due to the wide industrial application of process mining analyses. In this paper, we examine uncertain event data. Such data contain meta-attributes describing the amount of imprecision tied with attributes recorded in an event log. We provide examples of uncertain event data, present the state of the art in regard of uncertainty in process mining, and illustrate open challenges related to this research direction.

Mining Uncertain Event Data in Process Mining

Nowadays, more and more process data are automatically recorded by information systems, and made available in the form of event logs. Process mining techniques enable process-centric analysis of data, including automatically discovering process models and checking if event data conform to a certain model. In this paper we analyze the previously unexplored setting of uncertain event logs: logs where quantified uncertainty is recorded together with the corresponding data. We define a taxonomy of uncertain event logs and models, and we examine the challenges that uncertainty poses on process disc…

Conformance Checking over Uncertain Event Data

The strong impulse to digitize processes and operations in companies and enterprises have resulted in the creation and automatic recording of an increasingly large amount of process data in information systems. These are made available in the form of event logs. Process mining techniques enable the process-centric analysis of data, including automatically discovering process models and checking if event data conform to a given model. In this paper, we analyze the previously unexplored setting of uncertain event logs. In such event logs uncertainty is recorded explicitly, i.e., the time, activi…

Process Mining on Uncertain Event Data

With the widespread adoption of process mining in organizations, the field of process science is seeing an increase in the demand for ad-hoc analysis techniques of non-standard event data. An example of such data are uncertain event data: events characterized by a described and quantified attribute imprecision. This paper outlines a research project aimed at developing process mining techniques able to extract insights from uncertain data. We set the basis for this research topic, recapitulate the available literature, and define a future outlook.

事件合成系统中不确定规则的推理模型

A Model for Reasoning with Uncertain Rules in Event Composition Systems

近年来，人们越来越需要使用主动系统，即需要根据事件或环境变化自动采取行动的系统。这样的系统跨越许多领域，从活动数据库到驱动当今企业核心业务流程的应用程序。然而，在许多情况下，系统必须响应的事件不是由监视工具生成的，而是必须基于复杂的时间谓词从其他事件中推断出来的。此外，在许多应用中，这样的推断本质上是不确定的。在本文中，我们介绍了一个正式的框架知识表示和推理，使这样的事件推理。基于概率论，我们定义了相关不确定性的表示。此外，我们正式定义的概率空间，并显示如何相关的概率可以通过动态构建贝叶斯网络计算。据我们所知，这是第一个工作，使考虑到这种不确定性的背景下，积极的系统。因此，我们的贡献是双重的：我们正式定义的概率设置的事件组合的表示和语义，并显示如何将这些扩展的事件的发生概率的量化。这些结果使任何主动系统都能够处理这种不确定性。