12 citations · 39 across the 5 of their papers we have counts for
8 papers
TabEAno: Table to Knowledge Graph Entity Annotation
Phuc Nguyen, Natthawut Kertkeidkachorn, Ryutaro Ichise +1
In the Open Data era, a large number of table resources have been made available on the Web and data portals. However, it is difficult to directly utilize such data due to the ambi…
MTab: Matching Tabular Data to Knowledge Graph using Probability Models
Phuc Nguyen, Natthawut Kertkeidkachorn, Ryutaro Ichise +1
This paper presents the design of our system, namely MTab, for Semantic Web Challenge on Tabular Data to Knowledge Graph Matching (SemTab 2019). MTab combines the voting algorithm…
Combination of Unified Embedding Model and Observed Features for Knowledge Graph Completion
Takuma Ebisu, Ryutaro Ichise
Knowledge graphs are useful for many artificial intelligence tasks but often have missing data. Hence, a method for completing knowledge graphs is required. Existing approaches inc…
Graph Pattern Entity Ranking Model for Knowledge Graph Completion
Takuma Ebisu, Ryutaro Ichise
Knowledge graphs have evolved rapidly in recent years and their usefulness has been demonstrated in many artificial intelligence tasks. However, knowledge graphs often have lots of…
EmbNum: Semantic labeling for numerical values with deep metric learning
Phuc Nguyen, Khai Nguyen, Ryutaro Ichise +1
Semantic labeling for numerical values is a task of assigning semantic labels to unknown numerical attributes. The semantic labels could be numerical properties in ontologies, inst…
Deep Reinforcement Learning Boosted by External Knowledge
Nicolas Bougie, Ryutaro Ichise
Recent improvements in deep reinforcement learning have allowed to solve problems in many 2D domains such as Atari games. However, in complex 3D environments, numerous learning epi…