most citedCompositional Learning of Relation Path Embedding for Knowledge Base Completion

4 citations · 9 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CY20212 cited

Towards Algorithmic Transparency: A Diversity Perspective

Fausto Giunchiglia, Jahna Otterbacher, Styliani Kleanthous +4

As the role of algorithmic systems and processes increases in society, so does the risk of bias, which can result in discrimination against individuals and social groups. Research…

cs.LG20213 cited

Topological Regularization for Graph Neural Networks Augmentation

Rui Song, Fausto Giunchiglia, Ke Zhao +1

The complexity and non-Euclidean structure of graph data hinder the development of data augmentation methods similar to those in computer vision. In this paper, we propose a featur…

cs.LG2021

Human-in-the-loop Handling of Knowledge Drift

Andrea Bontempelli, Fausto Giunchiglia, Andrea Passerini +1

We introduce and study knowledge drift (KD), a complex form of drift that occurs in hierarchical classification. Under KD the vocabulary of concepts, their individual distributions…

cs.DB2021

Is your Schema Good Enough to Answer my Query?

Yuanwei Zhao, Lan Huang, Bo Wang +4

Ontology-based data integration has been one of the practical methodologies for heterogeneous legacy database integrated service construction. However, it is neither efficient nor…

cs.CL20164 cited

Compositional Learning of Relation Path Embedding for Knowledge Base Completion

Xixun Lin, Yanchun Liang, Fausto Giunchiglia +2

Large-scale knowledge bases have currently reached impressive sizes; however, these knowledge bases are still far from complete. In addition, most of the existing methods for knowl…