• English
  • Deutsch
  • Log In
    Password Login
    Research Outputs
    Fundings & Projects
    Researchers
    Institutes
    Statistics
Repository logo
Fraunhofer-Gesellschaft
  1. Home
  2. Fraunhofer-Gesellschaft
  3. Konferenzschrift
  4. An Approach for Ex-Post-Facto Analysis of Knowledge Graph-Driven Chatbots - The DBpedia Chatbot
 
  • Details
  • Full
Options
2020
Conference Paper
Title

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  
Mainwork
Chatbot Research and Design. Third International Workshop, CONVERSATIONS 2019  
Conference
International Workshop CONVERSATIONS 2019  
DOI
10.1007/978-3-030-39540-7_2
Language
English
Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS  
  • Cookie settings
  • Imprint
  • Privacy policy
  • Api
  • Contact
© 2024