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Maximal Marginal Relevance-Based Recommendation for Product Customisation

C.H. (Jack) Wu, Yue Wang*, Jie Ma

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    23 Citations (Scopus)
    38 Downloads (Pure)

    Abstract

    Customised product design is attracting increasing attention. However, consumers can be overwhelmed by the variety of products. To confront this challenge, this paper presents a two-step recommendation approach for customised products. First, an adaptive specification process captures customer requirements in an accelerated manner by presenting the most informative attribute for a customer to specify. Then, a maximal marginal relevance-based recommendation set is presented, based on the customer’s partial specifications. This process ensures broad coverage of customers’ needs by considering not only the relevance of each product to their requirements but also redundancy in the recommendation set.
    Original languageEnglish
    Article number1992018
    Pages (from-to)1-14
    Number of pages14
    JournalEnterprise Information Systems
    Volume17
    Issue number5
    Early online date24 Oct 2021
    DOIs
    Publication statusPublished - 4 May 2023

    Keywords

    • Customisation
    • probability relevance model
    • product recommendation

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