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Scalable Real-Time Confusion Detection for Personalized Onboarding Guides

Part of the Lecture Notes in Computer Science book series (LNISA,volume 12128)


Onboarding of new employees is a common process in all companies. Many hours of qualified employees’ time need to be invested to teach new employees how to use the company’s internal systems. This process can be significantly eased by onboarding solutions leveraging application guides. However, if not personalized, the guides can quickly become annoying to users. This can be overcome by employing emotion detection in real-time, but the solutions face several major challenges, such as scalability, detection time, or model retraining. In this paper, we describe how we tackled these challenges and implemented an emotion detection-based personalization module in the onboarding solution YesElf. The module leverages the mouse interaction data of users to detect their confusion. We show the scalability of our solution in the production environment which has been deployed to three customers with more than 200 concurrent users.


  • Affective computing
  • Confusion detection
  • Personalization
  • Scalability
  • Real-time detection
  • YesElf

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  • DOI: 10.1007/978-3-030-50578-3_18
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    Throughout the rest of the paper we use the word customer to denote the owner of the web application who decided to integrate the YesElf. Under the term user we understand the user of the customer’s application.

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    Under the term context we understand the URL for which the context help is displayed, as each guide is situated at a specific URL.

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This work was partially supported by the Slovak Research and Development Agency under the contracts No. APVV-15-0508, APVV-17-0267 and by the Scientific Grant Agency of the Slovak Republic, grants No. VG 1/0667/18 and VG 1/0725/19. The authors would also like to thank the company Brainware for supporting their research.

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Hucko, M., Moro, R., Bielikova, M. (2020). Scalable Real-Time Confusion Detection for Personalized Onboarding Guides. In: Bielikova, M., Mikkonen, T., Pautasso, C. (eds) Web Engineering. ICWE 2020. Lecture Notes in Computer Science(), vol 12128. Springer, Cham.

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