Authors:
A. Martínez-Rojas
1
;
A. Jiménez-Ramírez
1
;
J. G. Enríquez
1
and
D. Lizcano-Casas
2
Affiliations:
1
Departamento de Lenguajes y Sistemas Informáticos, Escuela Técnica Superior de Ingeniería Informática, Avenida Reina Mercedes, s/n. 41012, Sevilla, Spain
;
2
Universidad a Distancia de Madrid, UDIMA, Vía de Servicio A-6, 15, 28400 Collado Villalba, Madrid, Spain
Keyword(s):
Robotic Process Automation, Noise Filtering, Eye Tracker, Gaze Analysis, Human-Computer Interaction, Feature Extraction.
Abstract:
Business process analysis is a key factor in the lifecycle of Robotic Process Automation. Currently, task mining techniques provide mechanisms to analyze information about the process tasks to be automated, e.g., identify repetitive tasks or process variations. Existing proposals mainly rely on the user interactions with the UIs of the system (i.e., keyboard and mouse level) and information that can be gathered from them (e.g., the window name) which is stored in a UI event log. In some contexts, the latter information is limited because the system is accessed through virtualized environments (e.g., Citrix or Teamviewer). Other approaches extend the UI Log, including screenshots to address this issue. Regardless of the context, the aim is to store as much information as possible in the UI Log so that is can be analyzed later on, e.g., by extracting features from the screenshots. This amount of information can introduce much noise in the log that messes up what is relevant to the proc
ess. To amend this, the current approach proposes a method to include a gaze analyzer, which helps to identify which is process-relevant information between all the information. More precisely, the proposal extends the UI Log definition with the attention change level, which records when the user’s attention changes from one element on the screen to another. This paper sets the research settings for the approach and enumerates the future steps to conduct it.
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