In this paper, we present an improved graph-based translation model which segments an input graph into node-induced subgraphs by taking source context into ...
May 21, 2019 · In this paper, we present an improved graph-based translation model which segments an input graph into node-induced subgraphs by taking ...
Bibliographic details on Context-Aware Graph Segmentation for Graph-Based Translation.
This paper construct graphs which combine bigram and dependency relations and propose a graph-based translation model, which segments an input graph into ...
The graph is trained using GCN which accounts for the context of each tissue for the cancer grading and classification.
Missing: Translation. | Show results with:Translation.
Oct 22, 2024 · In this paper, we propose a novel Graph-based Context-Aware Recommendation Systems with Knowledge Graph to analyse and predict users' behaviours ...
Sep 3, 2024 · The integration of knowledge graphs with AI and machine learning technologies unlocks powerful capabilities for generating and adapting ...
Nov 9, 2022 · We present UTango, a machine learning (ML)-based approach that learns to untangle the changes in a commit. We develop a novel code change clustering learning ...
We introduce a novel context-aware clustering framework via contrastive graph learning, which reasons intra-class relationships and intra-class boundaries.
Missing: Translation. | Show results with:Translation.
This repo is to provide a list of literature regarding Deep Learning on Graphs for NLP. Content. 1. Knowledge Graph/Knowledge Base: (32).