Data-driven Product Functional Configuration: Patent Data and Hypergraph

Abstract The product functional configuration (PFC) is typically used by firms to satisfy the individual requirements of customers and realized based on market analysis. This study aims help analyze functions realize configurations using patent data. first proposes a patent-data-driven PFC method hypergraph network. It then constructs weighted network model optimize combination function quantity object from perspective big data, as follows: (1) knowledge contained in extracted. (2) constructed co-occurrence relationship between patents applicants. (3) weight are calculated applicant’s value. (4) A calculation developed. (5) frequent subgraph algorithm obtain optimal list. applied an innovative design process bathroom shower. results indicate that this can detach candidates develop multifunctional product.