5 citations · 7 across the 5 of their papers we have counts for
8 papers
Region-Based Merging of Open-Domain Terminological Knowledge
Zied Bouraoui, Sebastien Konieczny, Thanh Ma +2
This paper introduces a novel method for merging open-domain terminological knowledge. It takes advantage of the Region Connection Calculus (RCC5), a formalism used to represent re…
From Shallow to Deep Interactions Between Knowledge Representation, Reasoning and Machine Learning (Kay R. Amel group)
Zied Bouraoui, Antoine Cornuéjols, Thierry Denœux +9
This paper proposes a tentative and original survey of meeting points between Knowledge Representation and Reasoning (KRR) and Machine Learning (ML), two areas which have been deve…
Modelling Semantic Categories using Conceptual Neighborhood
Zied Bouraoui, Jose Camacho-Collados, Luis Espinosa-Anke +1
While many methods for learning vector space embeddings have been proposed in the field of Natural Language Processing, these methods typically do not distinguish between categorie…
Inducing Relational Knowledge from BERT
Zied Bouraoui, Jose Camacho-Collados, Steven Schockaert
One of the most remarkable properties of word embeddings is the fact that they capture certain types of semantic and syntactic relationships. Recently, pre-trained language models…
Learning Conceptual Space Representations of Interrelated Concepts
Zied Bouraoui, Steven Schockaert
Several recently proposed methods aim to learn conceptual space representations from large text collections. These learned representations asso- ciate each object from a given doma…
Modeling Semantic Relatedness using Global Relation Vectors
Shoaib Jameel, Zied Bouraoui, Steven Schockaert
Word embedding models such as GloVe rely on co-occurrence statistics from a large corpus to learn vector representations of word meaning. These vectors have proven to capture surpr…