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An Approach for Ex-Post-Facto Analysis of Knowledge Graph-Driven Chatbots - The DBpedia Chatbot

: Jalota, R.; Trivedi, P.; Maheshwari, G.; Ngonga Ngomo, A.-C.; Usbeck, R.


Chatbot Research and Design. Third International Workshop, CONVERSATIONS 2019 : Amsterdam, The Netherlands, November 19–20, 2019, Revised Selected Papers
Cham: Springer, 2020 (Lecture Notes in Computer Science 11970)
ISBN: 978-3-030-39540-7
ISBN: 978-3-030-39539-1
International Workshop CONVERSATIONS <3, 2019, Amsterdam>
Fraunhofer IAIS ()

As chatbots are gaining popularity for simplifying access to information and community interaction, it is essential to examine whether these agents are serving their intended purpose and catering to the needs of their users. Therefore, we present an approach to perform an ex-post-facto analysis over the logs of knowledge base-driven dialogue systems. Using the DBpedia Chatbot as our case study, we inspect three aspects of the interactions, (i) user queries and feedback, (ii) the bot’s response to these queries, and (iii) the overall flow of the conversations. We discuss key implications based on our findings. All the source code used for the analysis can be found at