Flexible Heuristics Miner (FHM)

One of the aims of process mining is to retrieve a process model from a given event log. However, current techniques have problems when mining processes that contain nontrivial constructs, processes that are low structured and/or dealing with the presence of noise in the event logs. To overcome thes...

Full description

Saved in:
Bibliographic Details
Main Authors: Weijters, A. J. M. M., Ribeiro, J. T. S.
Format: Conference Proceeding
Language:English
Subjects:
Business
Data mining
Heuristic algorithms
Noise
Process control
PROM
Semantics
Citations: Items that cite this one
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:One of the aims of process mining is to retrieve a process model from a given event log. However, current techniques have problems when mining processes that contain nontrivial constructs, processes that are low structured and/or dealing with the presence of noise in the event logs. To overcome these problems, a new process representation language is presented in combination with an accompanying process mining algorithm. The most significant property of the new representation language is in the way the semantics of splits and joins are represented; by using so-called split/join frequency tables. This results in easy to understand process models even in the case of non-trivial constructs, low structured domains and the presence of noise. This paper explains the new process representation language and how the mining algorithm works. The algorithm is implemented as a plug-in in the ProM framework. An illustrative example with noise and a real life log of a complex and low structured process are used to explicate the presented approach.
DOI:10.1109/CIDM.2011.5949453