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A Socially-Aware Conversational Recommender System for Personalized Recipe Recommendations

Published: 10 November 2020 Publication History

Abstract

One potential solution to help people change their eating behavior is to develop conversational systems able to recommend healthy recipes. Beyond the intrinsic quality of the recommendations themselves, various factors might also influence users? perception of a recommendation. Two of these factors are the conversational skills of the system and users' interaction modality. In this paper, we present Cora, a conversational system that recommends recipes aligned with its users? eating habits and current preferences. Users can interact with Cora in two different ways. They can select predefined answers by clicking on buttons to talk to Cora or write text in natural language. On the other hand, Cora can engage users through a social dialogue, or go straight to the point. We conduct an experiment to evaluate the impact of Cora's conversational skills and users' interaction mode on users' perception and intention to cook the recommended recipes. Our results show that a conversational recommendation system that engages its users through a rapport-building dialogue improves users' perception of the interaction as well as their perception of the system.

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      cover image ACM Conferences
      HAI '20: Proceedings of the 8th International Conference on Human-Agent Interaction
      November 2020
      304 pages
      ISBN:9781450380546
      DOI:10.1145/3406499
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      Published: 10 November 2020

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      Author Tags

      1. conversational recommender system
      2. healthcare
      3. recipe recommendations
      4. socially-aware

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      View all
      • (2024)A Healthy Food Recommendation System Using KNN Model and Elasticsearch With Quantum ComputingReal-World Applications of Quantum Computers and Machine Intelligence10.4018/979-8-3693-3601-4.ch001(1-16)Online publication date: 30-Jun-2024
      • (2024)Conversational Recommender System for Audio Listening Device Based on Ontology2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)10.1109/ICETSIS61505.2024.10459658(1449-1453)Online publication date: 28-Jan-2024
      • (2024)Promoting by Looking Into Friend Circles: An Inadequately-Labeled and Socially-Aware Financial Technique for Products RecommendationIEEE Access10.1109/ACCESS.2024.348807212(159833-159846)Online publication date: 2024
      • (2024)The effectiveness of personalised food choice advice tailored to an individual’s socio-demographic, cognitive characteristics, and sensory preferences.Appetite10.1016/j.appet.2024.107600(107600)Online publication date: Jul-2024
      • (2023)Avances en el aprovechamiento de biopolímeros y productos peruanosApplication of artificial intelligence techniques in studies on eating habitsRevista Científica de Sistemas e Informática10.51252/rcsi.v3i1.4893:1(e489)Online publication date: 20-Jan-2023
      • (2023)CRS-Que: A User-centric Evaluation Framework for Conversational Recommender SystemsACM Transactions on Recommender Systems10.1145/36315342:1(1-34)Online publication date: 2-Nov-2023
      • (2023)Meta-CRS: A Dynamic Meta-Learning Approach for Effective Conversational Recommender SystemACM Transactions on Information Systems10.1145/360480442:1(1-27)Online publication date: 17-Jun-2023
      • (2023)Expressing Robot’s Understanding of Human Preference Based on Successive Estimations during DialogInternational Journal of Human–Computer Interaction10.1080/10447318.2023.223219540:18(5139-5160)Online publication date: 10-Jul-2023
      • (2023)A systematic review on food recommender systemsExpert Systems with Applications10.1016/j.eswa.2023.122166(122166)Online publication date: Oct-2023
      • (2023)A novel healthy and time-aware food recommender system using attributed community detectionExpert Systems with Applications10.1016/j.eswa.2023.119719221(119719)Online publication date: Jul-2023
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