Leveraging process discovery with trace clustering and text mining for intelligent analysis of incident management processes

TLDR: This paper proposes a combination of trace clustering and text mining to enhance process discovery techniques with the purpose of retrieving more useful insights from process data.

Abstract: Recent years have witnessed the ability to gather an enormous amount of data in a large number of domains. Also in the field of business process management, there exists an urgent need to beneficially use these data to retrieve actionable knowledge about the actual way of working in the context of a certain business process. The research field concerned is process mining, which can be defined as a whole family of analysis techniques for extracting knowledge from information system event logs. In this paper, we present a solution strategy to leverage traditional process discovery techniques in the flexible environment of incident management processes. In such environments, it is typically observed that single model discovery techniques are incapable of dealing with the large number of different types of execution traces. Accordingly, we propose a combination of trace clustering and text mining to enhance process discovery techniques with the purpose of retrieving more useful insights from process data.

Figures

TABLE V EVENT LOG AND DISCOVERED PROCESS MODEL CHARACTERISTICS FOR STANDARD MRA CLUSTERING

TABLE IV EVENT LOG AND DISCOVERED PROCESS MODEL CHARACTERISTICS FOR SEMSUP-MRA CLUSTERING

TABLE VI FREQUENT WORD LIST

TABLE II EXCERPT OF EVENT LOG DATA

Fig. 1. Histogram of trace frequency intervals for the event log

TABLE I EXCERPT OF CASE DATA

Frequently asked questions

Q1. What contributions have the authors mentioned in the paper "Leveraging process discovery with trace clustering and text mining for intelligent analysis of incident management processes" ?

In this paper, the authors present a solution strategy to leverage traditional process discovery techniques in the flexible environment of incident management processes. Accordingly, the authors propose a combination of trace clustering and text mining to enhance process discovery techniques with the purpose of retrieving more useful insights from process data. 

Q2. What have the authors stated for future works in "Leveraging process discovery with trace clustering and text mining for intelligent analysis of incident management processes" ?

In future work, the authors plan to further develop the novel trace clustering technique.