Skip to main content

ClayBot: Increasing Human-Centricity in Conversational Recommender Systems

  • Conference paper
  • First Online:
The Semantic Web: ESWC 2023 Satellite Events (ESWC 2023)

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

Included in the following conference series:

  • 626 Accesses


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.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
USD 59.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 74.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others


  1. 1.

    ClayBot Alexa Skill page:

  2. 2.

    A video recording of the demo featuring the discussed example in Fig. 2 is available at:

  3. 3.

    The queries can be tested on the following SPARQL endpoint:


  1. Christensen, C., Hall, T., Dillon, K., Duncan, D.S.: Competing Against Luck: The Story of Innovation and Customer Choice. HarperBusiness, New York (2016)

    Google Scholar 

  2. Christensen, C., Hall, T., Dillon, K., Duncan, D.S.: Know your customers’ jobs to be done. Harv. Bus. Rev. 94(9), 54–62 (2016)

    Google Scholar 

  3. Gao, C., Lei, W., He, X., de Rijke, M., Chua, T.S.: Advances and challenges in conversational recommender systems: a survey. AI Open 2, 100–126 (2021)

    Article  Google Scholar 

  4. Jannach, D., Pu, P., Ricci, F., Zanker, M.: Recommender systems: trends and frontiers. AI Mag. 43(2), 145–150 (2022)

    Google Scholar 

  5. Moradizeyveh, S.: Intent Recognition in Conversational Recommender Systems (2022). arXiv:2212.03721 [cs]

  6. Norman, D.: The Design of Everyday Things. Basic Books, New York (2013)

    Google Scholar 

  7. Schuurmans, J., Frasincar, F.: Intent classification for dialogue utterances. IEEE Intell. Syst. 35(1), 82–88 (2020)

    Article  Google Scholar 

  8. Zablith, F.: ActionRec: toward action-aware recommender systems on the web. In: International Semantic Web Conference Demos - CEUR Proceedings, vol. 2980 (2021)

    Google Scholar 

Download references


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.

Author information

Authors and Affiliations


Corresponding author

Correspondence to Fouad Zablith .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

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.

Download citation

  • DOI:

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-43457-0

  • Online ISBN: 978-3-031-43458-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics