Abstract
Chatbots are nowadays being applied widely in different life domains. One major reason for this trend is the mature development process that is supported by large companies and sophisticated conversational platforms. However, the required development steps are mostly done manually while transforming existing knowledge bases into interaction configurations, s.t., algorithms integrated into the conversational platforms are enabled to learn the intended interaction patterns. However, already existing domain knowledge may get vanished while transforming a structured knowledge base into a “flat” text representation without references backwards. In this paper, we aim for an automatic process dedicated to generating interaction configurations for a conversational platform (Google Dialogflow) from an existing domain-specific knowledge base. Our ultimate goal is to generate chatbot configurations automatically, s.t., the quality and efficiency are increased.
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The data is available in our online appendix at https://doi.org/hnb3.
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Wittig, A., Perevalov, A., Both, A. (2022). Towards Bridging the Gap Between Knowledge Graphs and Chatbots. In: Di Noia, T., Ko, IY., Schedl, M., Ardito, C. (eds) Web Engineering. ICWE 2022. Lecture Notes in Computer Science, vol 13362. Springer, Cham. https://doi.org/10.1007/978-3-031-09917-5_21
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DOI: https://doi.org/10.1007/978-3-031-09917-5_21
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