Search Results for author: Derek Bridge

Found 9 papers, 2 papers with code

iSee: Advancing Multi-Shot Explainable AI Using Case-based Recommendations

no code implementations23 Aug 2024 Anjana Wijekoon, Nirmalie Wiratunga, David Corsar, Kyle Martin, Ikechukwu Nkisi-Orji, Chamath Palihawadana, Marta Caro-Martínez, Belen Díaz-Agudo, Derek Bridge, Anne Liret

The iSee platform is designed for the intelligent sharing and reuse of explanation experiences, using Case-based Reasoning to advance best practices in XAI.

Decision Making

Supplier Recommendation in Online Procurement

no code implementations2 Mar 2024 Victor Coscrato, Derek Bridge

It is vital that the most competitive suppliers are invited to bid for such contracts.

Recommendation Systems

Enhancing Recommendation Diversity by Re-ranking with Large Language Models

no code implementations21 Jan 2024 Diego Carraro, Derek Bridge

The literature reports many ways of measuring diversity and improving the diversity of a set of recommendations, most notably by re-ranking and selecting from a larger set of candidate recommendations.

Diversity Recommendation Systems +1

A User-Centered Investigation of Personal Music Tours

no code implementations16 Aug 2022 Giovanni Gabbolini, Derek Bridge

We assess the algorithms, we discuss attributes of the tours that the algorithms produce, we identify which attributes are desirable and which are not, and we enumerate several possible improvements to the algorithms, along with practical suggestions on how to implement the improvements.

Diversity Recommendation Systems

An Interpretable Music Similarity Measure Based on Path Interestingness

1 code implementation3 Aug 2021 Giovanni Gabbolini, Derek Bridge

The results highlight the validity of our approach to music similarity, and demonstrate that path interestingness scores can be the basis of an accurate and interpretable similarity measure.

Sudden Death: A New Way to Compare Recommendation Diversification

no code implementations31 Jul 2019 Derek Bridge, Mesut Kaya, Pablo Castells

This paper describes problems with the current way we compare the diversity of different recommendation lists in offline experiments.

Diversity

Denoising Dictionary Learning Against Adversarial Perturbations

no code implementations7 Jan 2018 John Mitro, Derek Bridge, Steven Prestwich

We show that after applying (DDL) the reconstruction of the original data point from a noisy

Denoising Dictionary Learning

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