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ClayBot: Increasing Human-Centricity in Conversational Recommender Systems

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The Semantic Web: ESWC 2023 Satellite Events (ESWC 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13998))

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Abstract

Conversational recommender systems are increasingly studied to provide more fine-tuned recommendations based on user preferences. However, most existing product recommendation approaches in online stores are designed to interact with people through questions that mainly focus on products or their attributes, and less on buyers’ core purchase needs. This work proposes ClayBot, a novel conversational recommendation agent, which aims to capture people’s intents and recommend products based on the jobs or actions that their buyers aim to do. Interactions with ClayBot are guided by an openly accessible knowledge graph, which connects a sample of computing products to the actions annotated in product reviews. A demonstration of ClayBot is presented as an Amazon Alexa Skill to showcase the feasibility of handling more human-centered interactions in the product recommendation and explanation process.

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Notes

  1. 1.

    ClayBot Alexa Skill page: https://www.amazon.com/dp/B0BX6LQQT7.

  2. 2.

    A video recording of the demo featuring the discussed example in Fig. 2 is available at: https://youtu.be/ZillD_f51MQ.

  3. 3.

    The queries can be tested on the following SPARQL endpoint:

    https://linked.aub.edu.lb/actionrec/sparql.

References

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Acknowledgments

This work was partially supported by the University Research Board of the American University of Beirut. Special thanks to Rayan Al Arab for his support in developing the tools.

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Correspondence to Fouad Zablith .

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Zablith, F. (2023). ClayBot: Increasing Human-Centricity in Conversational Recommender Systems. In: Pesquita, C., et al. The Semantic Web: ESWC 2023 Satellite Events. ESWC 2023. Lecture Notes in Computer Science, vol 13998. Springer, Cham. https://doi.org/10.1007/978-3-031-43458-7_12

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  • DOI: https://doi.org/10.1007/978-3-031-43458-7_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-43457-0

  • Online ISBN: 978-3-031-43458-7

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