Automated Refinement of Wikidata Taxonomy Using Large Language Models
An automated approach for refining the Wikidata taxonomy using a combination of Large Language Models (LLMs) and graph mining techniques, addressing issues like ambiguity, inconsistency, redundancy, and complexity.
多視点グラフ特徴伝播による効率的なエンティティアラインメントデコーディング手法
提案手法Triple Feature Propagation (TFP)は、エンティティ間、エンティティ-関係、関係-エンティティ、関係-トリプルの多視点の関係性を表現する一般化された隣接行列を用いて、ディリクレ・エネルギーの勾配流を最小化することで、効率的にエンティティ表現を再構築する。
Chain-like Rules Refinement into Tree-like Rules on Knowledge Graphs
Chain-like rules are refined into tree-like rules on knowledge graphs to enhance reasoning abilities and accuracy.
Knowledge Graph Summarization: iSummary Approach
iSummary presents a novel approach for constructing personalized summaries of Knowledge Graphs based on query logs, offering high-quality and efficient results.
Analyzing Inductive Knowledge Graph Completion with GNNs and Rules
Rule-based methods underperform due to limitations in ranking implausible entities and aggregating evidence, which can be addressed by integrating GNN strategies.
Chain-like Rules Refinement into Tree-like Rules on Knowledge Graphs
Tree-like rules improve reasoning ability over chain-like rules on knowledge graphs.
PyGraft: Configurable Generation of Synthetic Schemas and Knowledge Graphs
PyGraft is a Python-based tool that enables the generation of synthetic schemas and knowledge graphs, empowering researchers to create diverse datasets for benchmarking novel approaches in various fields.
iSummary: Workload-based, Personalized Summaries for Knowledge Graphs
Efficiently construct personalized summaries using query logs for high-quality results.
Entity Alignment with Unlabeled Dangling Cases: Investigating Detection and Alignment Frameworks
Proposing a novel GNN-based framework for entity alignment with unlabeled dangling cases, addressing challenges in detection and alignment.
Pseudo-Label Calibration Semi-supervised Multi-Modal Entity Alignment Study
PCMEA introduces a semi-supervised approach for multi-modal entity alignment, enhancing alignment quality through pseudo-label calibration and contrastive learning.
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