We propose a new model named Time-aware Interaction networks for Recommendation based on Heterogeneous information network (TIH4Rec) to improve performance.

This paper proposes a user-centric method for detecting anomalies in heterogeneous information networks, in which nodes and/or edges might be from different ...

In this paper, we propose a Bayesian Personalized Ranking(BPR) based machine learning method, called HeteLearn, to learn the weights of links in a HIN.

We develop a novel recommendation algorithm that integrates the attention mechanism, meta-paths, and neighbor node information (AMNRec).

This paper provides a comprehensive and systematic survey of HIN-based recommender systems, including four aspects: concepts, methods, applications, and ...

The major challenge of building recommender systems in hetero- geneous information networks is to systematically define features to represent the different ...

Jan 3, 2024 · Hu et al. proposed a deep neural network model of common attention mechanism based on heterogeneous information networks to solve the impact ...

In this paper, we study the entity recommendation problem in heterogeneous information networks. We propose to combine various relationship information from ...

Feb 15, 2024 · In this paper, we propose a new recommendation algorithm model, the interactive higher-order dual tower (IHDT), which improves current models by adding ...

Mar 19, 2024 · This study endeavors to amalgamate rich written reviews with heterogeneous information networks and analyze their effects on recommendation systems.