A survey on recommendation in process mining

Recommender systems have been widely applied in several domains to make informed decisions by recommending items that might be of interest. Considering recommendation during business process execution is also highly advantageous as the efficient suggestions about possible activities or resources can impact performance. However, deployment frameworks mining still needs more investigations identify current challenges enable practical application research findings and ensure a large-scale adoption this technique. Accordingly, systematic review conducted provide taxonomy published studies on process-aware recommender based specified criteria, including type perspective recommendation, list datasets evaluation metrics used setting PARS, implementation environments, different algorithms PARS. In regard, there are various insights extracted from study: (i) Most analysis domain descriptive predictive nature, (ii) an emerging area being evolving; majority proposals relate 2015 after that, (iii) due lack common protocol, datasets, metrics, most validated through experiments prototyping, with less tendency solution regarding real scenarios.