[3Pin1] インタラクティブ(1)

[3Pin1-03] Incorporating Knowledge Graph Embeddings into Latent Variable Models

〇Naoya Takeishi^1,2, Kosuke Akimoto¹ (1. The University of Tokyo, 2. RIKEN)

Keywords:Knowledge Graph, Knowledge Base, Latent Variable Model, Probabilistic Modeling, Unsupervised Learning

In this talk, we introduce an idea for incorporating information encoded in a knowledge graph to a latent variable model (LVM). We propose an extension of an LVM by two-view modeling, where the parameters and the latent variables of the LVM are shared between the original LVM and a probabilistic model for knowledge graph embedding. We specifically introduce how to incorporate a knowledge graph into probabilistic principal component analysis and show preliminary experimental results.