Academic Paper Recommendation Based On Heterogeneous Graph

Academic Paper Recommendation Based On Heterogeneous Graph – A heterogeneous graph representation based recommendation method named hgrec is proposed. In this paper, we propose a new recommendation method based on iterative heterogeneous graph learning on knowledge graphs (hgkr). Specifically, we design a deep. In this paper, we propose a novel recommendation method with a heterogeneous graph in which both citation and content knowledge are included.

A heterogeneous graph representation based recommendation method named hgrec is proposed that solves the personalized paper recommendation problem in the setting of. In this paper, we propose a new recommendation method based on iterative heterogeneous graph learning on knowledge graphs (hgkr). A hybrid paper recommendation method by using heterogeneous graph and metadata. This study aims to understand the behavior of academic job transition and hence recommend suitable institutions for phd graduates.

Academic Paper Recommendation Based On Heterogeneous Graph

Unlike existing works which only. We propose a novel method based on heterogeneous information networks for academic paper recommendation, referred to as hnpr. A heterogeneous graph representation based recommendation method named hgrec is proposed.

In this paper, we propose a novel recommendation method with a heterogeneous graph in which both citation and content knowledge are included. First, the author and paper pro les are constructed based on the extracted. To construct a heterogeneous graph with citation and content features in papers.