Addressing the cold-start problem of recommendation systems for financial products by using few-shot deep learning
TY Hung, SH Huang - Applied Intelligence, 2022 - Springer
With advances in machine learning, the application of financial services has become
increasingly intelligent. The artificial intelligence financial advisory and other customized …
increasingly intelligent. The artificial intelligence financial advisory and other customized …
Resource recommendation based on industrial knowledge graph in low-resource conditions
Resource recommendation is extremely challenging under low-resource conditions
because representation learning models require sufficient triplets for their training, and the …
because representation learning models require sufficient triplets for their training, and the …
Self‐supervised graph learning for occasional group recommendation
As an important branch in Recommender System, occasional group recommendation has
received more and more attention. In this scenario, each occasional group (cold‐start group) …
received more and more attention. In this scenario, each occasional group (cold‐start group) …
Addressing the cold start problem in privacy preserving content-based recommender systems using hypercube graphs
The initial interaction of a user with a recommender system is problematic because, in such
a so-called cold start situation, the recommender system has very little information about the …
a so-called cold start situation, the recommender system has very little information about the …
Exploring the Potential of the Hypercube-Based Model in Content-Based Recommender Systems
נועה תובל - 2024 - search.proquest.com
In this thesis I propose a new model which uses the concept of resolving set in a hypercube
graph, implemented through integer programming, to represent the users of a content-based …
graph, implemented through integer programming, to represent the users of a content-based …