Monitoring semantic relatedness and revealing fairness and biases through trend tests
An emerging application domain concerning content-based recommender systems provides a better consideration of the semantics behind textual descriptions. Traditional approaches often miss relevant information due to their sole focus on syntax. However, the Semantic Web community has enriched resourc...
Saved in:
Main Authors: | Jean-Rémi Bourguet, Adama Sow |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2025-06-01
|
Series: | International Journal of Information Management Data Insights |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2667096824000946 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Bridging Natural Language Processing and psycholinguistics: computationally grounded semantic similarity datasets for Basque and Spanish
by: Josu Goikoetxea, et al.
Published: (2024-11-01) -
A Review of Bias and Fairness in Artificial Intelligence
by: Rubén González-Sendino, et al.
Published: (2025-01-01) -
Un uso sostenible de WordNet en la inteligencia artificial
by: Carlos Periñán-Pascual
Published: (2023-12-01) -
Instances of bias: the gendered semantics of generic masculines in German revealed by instance vectors
by: Schmitz Dominic
Published: (2024-11-01) -
Students’ motivation and engagement in interprofessional education: the mediating role of peer relatedness
by: Fraide A. Ganotice Jr, et al.
Published: (2024-12-01)