Towards a framework for classifying chatbots

Daniel Braun, Florian Matthes

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

14 Scopus citations

Abstract

From sophisticated personal voice assistants like Siri or Alexa to simplistic keyword-based search bots, today, the label “chatbot” is used broadly for all kinds of systems that use natural language as input. However, the systems summarized under this term are so diverse, that they often have very little in common with regard to technology, usage, and their theoretical background. In order to make such systems more comparable, we propose a framework that classifies chatbots based on six categories, which allow a meaningful comparison based on features which are relevant for developers, scientists, and users. Ultimately, we hope to support the scientific discourse, as well as the development of chatbots, by providing an instrument to classify and analyze different groups of chatbot systems regarding their requirements, possible evaluation strategies, available toolsets, and other common features.

Original languageEnglish
Title of host publicationICEIS 2019 - Proceedings of the 21st International Conference on Enterprise Information Systems
EditorsJoaquim Filipe, Michal Smialek, Alexander Brodsky, Slimane Hammoudi
PublisherSciTePress
Pages484-489
Number of pages6
ISBN (Electronic)9789897583728
DOIs
StatePublished - 2019
Event21st International Conference on Enterprise Information Systems, ICEIS 2019 - Heraklion, Crete, Greece
Duration: 3 May 20195 May 2019

Publication series

NameICEIS 2019 - Proceedings of the 21st International Conference on Enterprise Information Systems
Volume1

Conference

Conference21st International Conference on Enterprise Information Systems, ICEIS 2019
Country/TerritoryGreece
CityHeraklion, Crete
Period3/05/195/05/19

Keywords

  • Chatbot
  • Classification framework
  • Conversational interface
  • Natural language interface

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