Clustering-Based Predictive Process Monitoring

Business process enactment is generally supported by information systems that record data about process executions, which can be extracted as event logs. Predictive process monitoring is concerned with exploiting such event logs to predict how running (uncompleted) cases will unfold up to their completion. In this paper, we propose a predictive process monitoring framework for estimating the probability that a given predicate will be fulfilled upon completion of a running case. The predicate can be, for example, a temporal logic constraint or a time constraint, or any predicate that can be evaluated over a completed trace. The framework takes into account both the sequence of events observed in the current trace, as well as data attributes associated to these events. The prediction problem is approached in two phases. First, prefixes of previous traces are clustered according to control flow information. Secondly, a classifier is built for each cluster using event data to discriminate between fulfillments and violations. At runtime, a prediction is made on a running case by mapping it to a cluster and applying the corresponding classifier. The framework has been implemented in the ProM toolset and validated on a log pertaining to the treatment of cancer patients in a large hospital

Run-time prediction of business process indicators using evolutionary decision rules

Predictive monitoring of business processes is a challenging topic of process mining which is concerned with the prediction of process indicators of running process instances. The main value of predictive monitoring is to provide information in order to take proactive and corrective actions to improve process performance and mitigate risks in real time. In this paper, we present an approach for predictive monitoring based on the use of evolutionary algorithms. Our method provides a novel event window-based encoding and generates a set of decision rules for the run-time prediction of process indicators according to event log properties. These rules can be interpreted by users to extract further insight of the business processes while keeping a high level of accuracy. Furthermore, a full software stack consisting of a tool to support the training phase and a framework that enables the integration of run-time predictions with business process management systems, has been developed. Obtained results show the validity of our proposal for two large real-life datasets: BPI Challenge 2013 and IT Department of Andalusian Health Service (SAS).Ministerio de Economía y Competitividad TIN2015-70560-RJunta de Andalucía P12TIC-186

Lenguaje de Consultas para la Gestión de Acontecimientos

El objetivo de esta tesis es la definición de un lenguaje de consultas para el acceso a la información almacenada en un tipo de estructura de persistencia denominado Base de Acontecimientos. Una base de acontecimientos es una estructura de persistencia cuya unidad mínima de información es el Acontecimiento. El concepto Acontecimiento se define como “Una pieza de información concreta, identificable e indivisible que contiene aspectos organizados de acuerdo a tres dimensiones: guía, estructura y comportamiento”. En el contexto de esta tesis, estructura refiere a los objetos que permiten representar un determinado Universo del Discurso (Universe of Discourse; UoD), guía hace referencia a las posibles acciones que pueden afectar a los citados objetos y, por último, comportamiento refiere al efecto producido sobre un objeto cuando se le aplica una determinada acción. Así pues, una base de acontecimientos se define como “Un tipo de estructura de información que registra acontecimientos que han tenido lugar a lo largo del tiempo”. A través de esta tesis se define (1) un framework o sistema de conceptos y reglas que permiten representar estructuralmente, en un Universo del Discurso, los elementos a utilizar en la gestión de acontecimientos, (2) un metamodelo que normaliza los conceptos aplicados en las estrategias de diseño que facilitan la construcción de bases de acontecimientos, y (3) un lenguaje de consultas para facilitar el acceso a la información almacenada en bases de acontecimientos. El lenguaje, como parte de los objetivos pretendidos, posibilita no sólo acceder a la información almacenada en una base de acontecimientos, sino también a la información que describe la estructura de la misma que se encuentra almacenada en un componente del framework denominado Diccionario