Leveraging Semantic Information for Enhanced Community Search in Heterogeneous Graphs
Sign Up to like & getrecommendations! Published in 2024 at "Data Science and Engineering"
DOI: 10.1007/s41019-024-00244-z
Abstract: Community search (CS) is a vital research area in network science that focuses on discovering personalized communities for query vertices from graphs. However, existing CS methods mainly concentrate on homogeneous or simple attributed graphs, often… read more here.
Keywords: community search; community; heterogeneous graphs; semantic information ... See more keywords
Integrating Heterogeneous Graphs Using Graph Transformer Encoder for Solving Math Word Problems
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Access"
DOI: 10.1109/access.2023.3257571
Abstract: This paper introduces a novel method that integrates structural information with training deep neural models to solve math word problems. Prior works adopt the graph structure to represent rich information residing in the input sentences.… read more here.
Keywords: heterogeneous graphs; graph; transformer encoder; math word ... See more keywords
Few-Shot Causal Representation Learning for Out-of-Distribution Generalization on Heterogeneous Graphs
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Transactions on Knowledge and Data Engineering"
DOI: 10.1109/tkde.2025.3531469
Abstract: To address the issue of label sparsity in heterogeneous graphs (HGs), heterogeneous graph few-shot learning (HGFL) has recently emerged. HGFL aims to extract meta-knowledge from source HGs with rich-labeled data and transfers it to a… read more here.
Keywords: shot; distribution; generalization; causal ... See more keywords