Barko-Sherif, S., Elsweiler, D. and Harvey, M. (2020) Conversational agents for recipe recommendation. In: Proceedings of the 2020 Conference on Human Information Interaction and Retrieval. 5th ACM SIGIR Conference on Human Information Interaction and Retrieval (CHIIR '20), 14-18 Mar 2020, Vancouver, BC, Canada. Association for Computing Machinery (ACM) , pp. 73-82. ISBN 9781450368926
Abstract
As technology improves, the use of conversational agents to help users solve information seeking tasks is becoming ever more prevalent. To date we know little about how people behave with such systems, particularly in diverse contexts and for different tasks, their specific needs or how best to support these. By employing a Wizard of Oz (WoZ) methodology and developing a conversational framework, in this work we study how participants (n=28) interact with such a system in an attempt to solve recipe recommendation tasks. Our results are mostly encouraging for the future development of conversational agents in this context, however, they also provide insights into the complexities of building such a system that could convincingly engage with users in productive, human-like conversations.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2020 ACM. This is an author-produced version of a paper subsequently published in CHIIR '20: Proceedings of the 2020 Conference on Human Information Interaction and Retrieval. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | conversational agents; recipe recommendation |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Social Sciences (Sheffield) > Information School (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 12 Feb 2020 15:15 |
Last Modified: | 18 Mar 2020 14:16 |
Status: | Published |
Publisher: | Association for Computing Machinery (ACM) |
Refereed: | Yes |
Identification Number: | 10.1145/3343413.3377967 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:156597 |