Abstract
A conversational system is a core component needed to create a chatbot, one incredibly popular form of conversational interface, without any programming knowledge, made possible by different toolkits and cloud-based Natural Language Understanding (NLU) services. However, these NLU services provide curatorial tools that do not always follow mental models resembling that of the content curators. Moreover, we present an interface for content curators that are aligned with concepts management embedded in taxonomies. We conducted a workshop to understand content creators’ work practices, created a prototype interface, and conducted a user evaluation to identify usability and productivity aspects. Based on our prototype’s evaluation insights, we provide implications for designing user interfaces of NLU services to support curators’ work practices and enhance collaboration.
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Pichiliani, M. et al. (2022). A User Interface with Taxonomy Features for Content Curators of Chatbots. In: Stephanidis, C., Antona, M., Ntoa, S. (eds) HCI International 2022 Posters. HCII 2022. Communications in Computer and Information Science, vol 1580. Springer, Cham. https://doi.org/10.1007/978-3-031-06417-3_59
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DOI: https://doi.org/10.1007/978-3-031-06417-3_59
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