Uncertainty-Aware Fuzzy Centrality Measures for Influential Node Identification: A Structural Modeling Approach Toward E-Commerce Applications
For e-commerce platforms, it addresses the problem of identifying influential entities under noisy, implicit interaction data, but the approach is incremental.
The paper proposes uncertainty-aware fuzzy centrality measures to identify influential nodes in e-commerce networks with uncertain interactions, demonstrating improved accuracy over deterministic methods in synthetic and real-world datasets.
In recent years, e-commerce platforms have become one of the most prominent examples of large-scale interaction networks, where understanding influence dynamics among users, products, and digital entities is essential for applications such as online marketing, recommendation systems, and customer behavior analysis. A key challenge in these platforms is that interactions are often uncertain, noisy, and inferred from implicit signals rather than explicitly defined relationships. This uncertainty cannot be effectively captured using deterministic network models...