Search Results for author:
Found 7 papers, 5 papers with code
Do Similar Entities have Similar Embeddings?
A common tacit assumption is the KGE entity similarity assumption, which states that these KGEMs retain the graph's structure within their embedding space, \textit{i. e.}, position similar entities within the graph close to one another.
PyGraft: Configurable Generation of Synthetic Schemas and Knowledge Graphs at Your Fingertips
In some data-sensitive fields such as education or medicine, access to public datasets is even more limited.
Schema First! Learn Versatile Knowledge Graph Embeddings by Capturing Semantics with MASCHInE
These models learn a vector representation of knowledge graph entities and relations, a. k. a.
Treat Different Negatives Differently: Enriching Loss Functions with Domain and Range Constraints for Link Prediction
In an extensive and controlled experimental setting, we show that the proposed loss functions systematically provide satisfying results which demonstrates both the generality and superiority of our proposed approach.
Sem@$K$: Is my knowledge graph embedding model semantic-aware?
That is why, in this paper, we extend our previously introduced metric Sem@K that measures the capability of models to predict valid entities w. r. t.
Use of Bayesian Network characteristics to link project management maturity and risk of project overcost
The project management field has the imperative to increase the project probability of success.
Results of multi-agent system and ontology to manage ideas and represent knowledge in a challenge of creativity
This article is about an intelligent system to support ideas management as a result of a multi-agent system used in a distributed system with heterogeneous information as ideas and knowledge, after the results about an ontology to describe the meaning of these ideas.
