most citedA Personalized Recommender System Based-on Knowledge Graph Embeddings

11 citations · 27 across the 7 of their papers we have counts for

collaborators

7 papers

cs.DB2024

Exploring Weighted Property Approaches for RDF Graph Similarity Measure

Ngoc Luyen Le, Marie-Hélène Abel, Philippe Gouspillou

Measuring similarity between RDF graphs is essential for various applications, including knowledge discovery, semantic web analysis, and recommender systems. However, traditional s…

cs.IR2024

Combining Embedding-Based and Semantic-Based Models for Post-hoc Explanations in Recommender Systems

Ngoc Luyen Le, Marie-Hélène Abel, Philippe Gouspillou

In today's data-rich environment, recommender systems play a crucial role in decision support systems. They provide to users personalized recommendations and explanations about the…

cs.IR2023

Designing a User Contextual Profile Ontology: A Focus on the Vehicle Sales Domain

Ngoc Luyen Le, Marie-Hélène Abel, Philippe Gouspillou

In the digital age, it is crucial to understand and tailor experiences for users interacting with systems and applications. This requires the creation of user contextual profiles t…

cs.IR20238 cited

A Constraint-based Recommender System via RDF Knowledge Graphs

Ngoc Luyen Le, Marie-Hélène Abel, Philippe Gouspillou

Knowledge graphs, represented in RDF, are able to model entities and their relations by means of ontologies. The use of knowledge graphs for information modeling has attracted inte…

cs.AI202311 cited

A Personalized Recommender System Based-on Knowledge Graph Embeddings

Ngoc Luyen Le, Marie-Hélène Abel, Philippe Gouspillou

Knowledge graphs have proven to be effective for modeling entities and their relationships through the use of ontologies. The recent emergence in interest for using knowledge graph…

cs.IR20238 cited

Improving Semantic Similarity Measure Within a Recommender System Based-on RDF Graphs

Ngoc Luyen Le, Marie-Hélène Abel, Philippe Gouspillou

In today's era of information explosion, more users are becoming more reliant upon recommender systems to have better advice, suggestions, or inspire them. The measure of the seman…