How do conversational case-based reasoning systems interact with their users: A literature review
Research output: Contribution to journal › Research article › Contributed › peer-review
Contributors
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.
Details
Original language | English |
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Pages (from-to) | 1544-1563 |
Number of pages | 20 |
Journal | Behaviour & information technology : BIT : an international journal on the human aspects of computing |
Volume | 40 |
Issue number | 14 |
Publication status | Published - 2021 |
Peer-reviewed | Yes |
External IDs
Scopus | 85085029376 |
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Keywords
ASJC Scopus subject areas
Keywords
- conversational case-based reasoning, dialogue system, explainable artificial intelligence, human-machine cooperation, mixed initiative, question selection