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  4. An Approach for Ex-Post-Facto Analysis of Knowledge Graph-Driven Chatbots - The DBpedia Chatbot
 
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2020
Conference Paper
Titel

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

Abstract
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 https://github.com/dice-group/DBpedia-Chatlog-Analysis.
Author(s)
Jalota, R.
Trivedi, Priyansh
Maheshwari, Gaurav
Ngonga Ngomo, Axel-Cyrille
Usbeck, Ricardo
Hauptwerk
Chatbot Research and Design. Third International Workshop, CONVERSATIONS 2019
Konferenz
International Workshop CONVERSATIONS 2019
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DOI
10.1007/978-3-030-39540-7_2
Language
English
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Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS
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