Derek Bridge
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View article: iSee: Advancing Multi-Shot Explainable AI Using Case-Based Recommendations
iSee: Advancing Multi-Shot Explainable AI Using Case-Based Recommendations Open
Explainable AI (XAI) can greatly enhance user trust and satisfaction in AI-assisted decision-making processes. Recent findings suggest that a single explainer may not meet the diverse needs of multiple users in an AI system; indeed, even i…
View article: Enhancing Recommendation Diversity by Re-ranking with Large Language Models
Enhancing Recommendation Diversity by Re-ranking with Large Language Models Open
Recommender Systems (RS) should provide diverse recommendations, not just relevant ones. Diversity helps handle uncertainty and offers users meaningful choices. The literature proposes various methods to improve diversity, most notably by …
View article: iSee: Advancing Multi-Shot Explainable AI Using Case-based Recommendations
iSee: Advancing Multi-Shot Explainable AI Using Case-based Recommendations Open
Explainable AI (XAI) can greatly enhance user trust and satisfaction in AI-assisted decision-making processes. Recent findings suggest that a single explainer may not meet the diverse needs of multiple users in an AI system; indeed, even i…
View article: Surveying More Than Two Decades of Music Information Retrieval Research on Playlists
Surveying More Than Two Decades of Music Information Retrieval Research on Playlists Open
In this article, we present an extensive survey of music information retrieval (MIR) research into music playlists. Our survey spans more than 20 years, and includes around 300 papers about playlists, with over 70 supporting sources. It is…
View article: iSee: A case-based reasoning platform for the design of explanation experiences
iSee: A case-based reasoning platform for the design of explanation experiences Open
Explainable Artificial Intelligence (XAI) is an emerging field within Artificial Intelligence (AI) that has provided many methods that enable humans to understand and interpret the outcomes of AI systems. However, deciding on the best expl…
View article: XEQ Scale for Evaluating XAI Experience Quality
XEQ Scale for Evaluating XAI Experience Quality Open
Explainable Artificial Intelligence (XAI) aims to improve the transparency of autonomous decision-making through explanations. Recent literature has emphasised users' need for holistic "multi-shot" explanations and personalised engagement …
View article: Supplier Recommendation in Online Procurement
Supplier Recommendation in Online Procurement Open
Supply chain optimization is key to a healthy and profitable business. Many companies use online procurement systems to agree contracts with suppliers. It is vital that the most competitive suppliers are invited to bid for such contracts. …
View article: Enhancing Recommendation Diversity by Re-ranking with Large Language Models
Enhancing Recommendation Diversity by Re-ranking with Large Language Models Open
It has long been recognized that it is not enough for a Recommender System (RS) to provide recommendations based only on their relevance to users. Among many other criteria, the set of recommendations may need to be diverse. Diversity is o…
View article: Deliverables of Milestone 3 for iSee project
Deliverables of Milestone 3 for iSee project Open
iSee Deliverables of Milestone 3 Belen Diaz-Agudo; Nirmalie Wiratunga; Anne Liret; Derek Bridge; Juan A. Recio-García; Marta Caro; Jesus Darias Goitia; Anjana Wijekoon; David Corsar; Kyle Martin; Ike Nkisi-Orji; Craig Piri…
View article: Estimating and Evaluating the Uncertainty of Rating Predictions and Top-n Recommendations in Recommender Systems
Estimating and Evaluating the Uncertainty of Rating Predictions and Top-n Recommendations in Recommender Systems Open
Uncertainty is a characteristic of every data-driven application, including recommender systems. The quantification of uncertainty can be key to increasing user trust in recommendations or choosing which recommendations should be accompani…
View article: Recommendation Uncertainty in Implicit Feedback Recommender Systems
Recommendation Uncertainty in Implicit Feedback Recommender Systems Open
A Recommender System’s recommendations will each carry a certain level of uncertainty. The quantification of this uncertainty can be useful in a variety of ways. Estimates of uncertainty might be used externally; for example, showing them …
View article: Predicting the Listening Contexts of Music Playlists Using Knowledge Graphs
Predicting the Listening Contexts of Music Playlists Using Knowledge Graphs Open
Playlists are a major way of interacting with music, as evidenced by the fact that streaming services currently host billions of playlists. In this content overload scenario, it is crucial to automatically characterise playlists, so that m…
View article: CBR Driven Interactive Explainable AI
CBR Driven Interactive Explainable AI Open
View article: Deliverables of Milestone 2 of iSee project
Deliverables of Milestone 2 of iSee project Open
iSee Deliverables of Milestone 2 https://isee4xai.com/ 10.5281/zenodo.7472464 Belen Diaz-Agudo; Nirmalie Wiratunga; Anne Liret; Derek Bridge; Juan A. Recio-García; Marta Caro; Jesus Darias Goitia; Anjana Wijekoon; David Co…
View article: A User-Centered Investigation of Personal Music Tours
A User-Centered Investigation of Personal Music Tours Open
Streaming services use recommender systems to surface the right music to\nusers. Playlists are a popular way to present music in a list-like fashion, ie\nas a plain list of songs. An alternative are tours, where the songs alternate\nsegues…
View article: iSee Deliverables of Milestone 1
iSee Deliverables of Milestone 1 Open
iSee Milestone 1 (month 9) - December 2021 Work packages: WP1, WP2, WP3, WP5, WP6 Index D2.3. Software. Retrieval-only iSee CBR system (iSee v1) (UCM, SW…
View article: iSee Deliverables of Milestone 0
iSee Deliverables of Milestone 0 Open
D1.1. Ontology requirements completed [RGU] D2.1a. Software development plan [UCM] D5.1a. Systematic review of evaluation measurements [RGU/BT] D6.1. iSee web and community netwo…
View article: An interpretable music similarity measure based on path interestingness
An interpretable music similarity measure based on path interestingness Open
We introduce a novel and interpretable path-based music similarity measure. Our similarity measure assumes that items, such as songs and artists, and information about those items are represented in a knowledge graph. We find paths in the …
View article: Play It Again, Sam! Recommending Familiar Music in Fresh Ways
Play It Again, Sam! Recommending Familiar Music in Fresh Ways Open
In the music domain, repeated consumption is not uncommon. In this work, we explore how to recommend familiar music in fresh ways. Specifically, we design algorithms that can produce 'tours' through a small personal collection of songs. Th…
View article: An Interpretable Music Similarity Measure Based on Path Interestingness
An Interpretable Music Similarity Measure Based on Path Interestingness Open
We introduce a novel and interpretable path-based music similarity measure. Our similarity measure assumes that items, such as songs and artists, and information about those items are represented in a knowledge graph. We find paths in the …
View article: A sampling approach to Debiasing the offline evaluation of recommender systems
A sampling approach to Debiasing the offline evaluation of recommender systems Open
View article: Generating Interesting Song-to-Song Segues With Dave
Generating Interesting Song-to-Song Segues With Dave Open
We introduce a novel domain-independent algorithm for generating interesting item-to-item textual connections, or segues. Pivotal to our contribution is the introduction of a scoring function for segues, based on their "interestingness". W…
View article: Feature based and feature free textual CBR: a comparison in spam filtering
Feature based and feature free textual CBR: a comparison in spam filtering Open
Spam filtering is a text classification task to which Case-Based Reasoning (CBR) has been successfully applied. We describe the ECUE system, which classifies emails using a feature-based form of textual CBR. Then, we describe an alternativ…
View article: dave-dataset
dave-dataset Open
This is the dataset of Giovanni Gabbolini and Derek Bridge's "Generating Interesting Song-to-Song Segues With Dave". Please find the official central repository here.
View article: dave-dataset
dave-dataset Open
This is the dataset of Giovanni Gabbolini and Derek Bridge's "Generating Interesting Song-to-Song Segues With Dave". Please find the official central repository here.
View article: Ensuring Fairness in Group Recommendations by Rank-Sensitive Balancing of Relevance
Ensuring Fairness in Group Recommendations by Rank-Sensitive Balancing of Relevance Open
For group recommendations, one objective is to recommend an ordered set of items, a top-N , to a group such that each individual recommendation is relevant for everyone. A common way to do this is to select items on which the group can agr…
View article: Case-Based Reuse of Software Examplets
Case-Based Reuse of Software Examplets Open
View article: Debiased offline evaluation of recommender systems
Debiased offline evaluation of recommender systems Open
Offline evaluation of recommender systems mostly relies on historical data, which is often biased by many confounders. In such data, user-item interactions are Missing Not At Random (MNAR). Measures of recommender system performance on MNA…
View article: Navigation-by-preference
Navigation-by-preference Open
We present Navigation-by-Preference, n-by-p, a new conversational recommender that uses what the literature calls preference-based feedback. Given a seed item, the recommender helps the user navigate through item space to find an item that…
View article: Sudden Death: A New Way to Compare Recommendation Diversification
Sudden Death: A New Way to Compare Recommendation Diversification Open
This paper describes problems with the current way we compare the diversity of different recommendation lists in offline experiments. We illustrate the problems with a case study. We propose the Sudden Death score as a new and better way o…