Process mining on noisy logs - Can log sanitization help to improven performance?

摘要

Process mining techniques are designed to read process logs and extract process models from them. However, real world logs are often noisy and such logs produce bad, spaghetti-like process models. We propose a technique to sanitize noisy logs by first building a classifier on a subset of the log, and applying the classifier rules to remove noisy traces from the log. The improvement in the quality of the resulting process models is evaluated on synthetic logs from benchmark models of increasing c