3 papers
cs.IR2025
Extracting Document Relations from Search Corpus by Marginalizing over User Queries
Yuki Iwamoto, Kaoru Tsunoda, Ken Kaneiwa
Understanding relationships between documents in large-scale corpora is essential for knowledge discovery and information organization. However, existing approaches rely heavily on…
cs.AI2024
A Self-matching Training Method with Annotation Embedding Models for Ontology Subsumption Prediction
Yukihiro Shiraishi, Ken Kaneiwa
Recently, ontology embeddings representing entities in a low-dimensional space have been proposed for ontology completion. However, the ontology embeddings for concept subsumption…
cs.LG2022
Multi-duplicated Characterization of Graph Structures using Information Gain Ratio for Graph Neural Networks
Yuga Oishi, Ken kaneiwa
Various graph neural networks (GNNs) have been proposed to solve node classification tasks in machine learning for graph data. GNNs use the structural information of graph data by…