Little information is available regarding which types of failures robots experience in domestic settings. To further the community's knowledge, we manually classified 3062 customer reviews of robotic vacuum cleaners on Amazon.com. The resulting database was analyzed and used to create a Natural Language Processing (NLP) model capable of predicting whether a review contains a description of a failure or not. The current work describes the initial analysis and model development process as well as preliminary findings.
|Title of host publication||HRI 2020 - Companion of the 2020 ACM/IEEE International Conference on Human-Robot Interaction|
|Publisher||IEEE Computer Society|
|Number of pages||3|
|State||Published - 23 Mar 2020|
|Event||15th Annual ACM/IEEE International Conference on Human Robot Interaction, HRI 2020 - Cambridge, United Kingdom|
Duration: 23 Mar 2020 → 26 Mar 2020
|Name||ACM/IEEE International Conference on Human-Robot Interaction|
|Conference||15th Annual ACM/IEEE International Conference on Human Robot Interaction, HRI 2020|
|Period||23/03/20 → 26/03/20|
Bibliographical noteFunding Information:
The first author is supported by The Helmsley Charitable Trust through the Agricultural, Biological, Cognitive Robotics Initiative and the Marcus Endowment Fund, and by Ben-Gurion University through the High-tech, Bio-tech and Chemo-tech Scholarship.
© 2020 ACM.
- Human-robot interaction
- Social network analysis
- User satisfaction