EconPapers    
Economics at your fingertips  
 

How do conversational case-based reasoning systems interact with their users: a literature review

Stefanie Hillig and Romy Müller

Behaviour and Information Technology, 2021, vol. 40, issue 14, 1544-1563

Abstract: Conversational case-based reasoning (CCBR) systems retrieve past cases that are similar to a current problem by eliciting situation descriptions in interactive dialogues with their users. To find out how such human-machine cooperation is put into practice, the present article reviews the CCBR literature and extracts a list of dialogue principles – interaction techniques by means of which CCBR systems communicate with their users. Seven dialogue principles are identified and explained: mixed initiative, question selection and ordering, dealing with abstraction and expertise, explanations, visualisation and highlighting, dialogue termination, and evaluation support. The results reveal that current CCBR systems already make great efforts to put user needs into the centre of the interaction. At the same time, the current implementation of dialogue principles that adjust CCBR systems to user needs raise questions about who should be in control of these adjustments, what levels of human-computer interaction should be adjusted, and what goals should guide adjustment decisions. Moreover, the present review highlights a number of limitations concerning the methodology and contents of CCBR research, and points out questions for future research on human-computer interaction in CCBR systems.

Date: 2021
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/0144929X.2020.1767207 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:tbitxx:v:40:y:2021:i:14:p:1544-1563

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/tbit20

DOI: 10.1080/0144929X.2020.1767207

Access Statistics for this article

Behaviour and Information Technology is currently edited by Dr Panos P Markopoulos

More articles in Behaviour and Information Technology from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().

 
Page updated 2025-03-20
Handle: RePEc:taf:tbitxx:v:40:y:2021:i:14:p:1544-1563