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

2 Downloads (Pure)


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
Pages (from-to)1-14
Number of pages14
JournalEnterprise Information Systems
Early online date24 Oct 2021
Publication statusE-pub ahead of print - 24 Oct 2021


Dive into the research topics of 'Maximal Marginal Relevance-Based Recommendation for Product Customisation'. Together they form a unique fingerprint.

Cite this