arXiv:1910.09532
공식 코드 · Papers with Code
Building Dynamic Knowledge Graphs from Text-based Games
원문 초록
We are interested in learning how to update Knowledge Graphs (KG) from text. In this preliminary work, we propose a novel Sequence-to-Sequence (Seq2Seq) architecture to generate elementary KG operations. Furthermore, we introduce a new dataset for KG extraction built upon text-based game transitions (over 300k data points). We conduct experiments and discuss the results.
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Knowledge Graph-based Retrieval-Augmented Generation for Schema Matching
Graph Collaborative Attention Network for Link Prediction in Knowledge Graphs
A Multi-Expert Structural-Semantic Hybrid Framework for Unveiling Historical Patterns in Temporal Knowledge Graphs
Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering
Bridging RDF Knowledge Graphs with Graph Neural Networks for Semantically-Rich Recommender Systems
Paths to Causality: Finding Informative Subgraphs Within Knowledge Graphs for Knowledge-Based Causal Discovery
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