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08/15/2023
Impression-Aware Recommender Systems
Novel data sources bring new opportunities to improve the quality of rec...
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08/03/2023
Benchmarking Adaptative Variational Quantum Algorithms on QUBO Instances
In recent years, Variational Quantum Algorithms (VQAs) have emerged as a...
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11/05/2022
Feature Selection for Classification with QAOA
Feature selection is of great importance in Machine Learning, where it c...
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05/09/2022
Towards Feature Selection for Ranking and Classification Exploiting Quantum Annealers
Feature selection is a common step in many ranking, classification, or p...
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01/20/2022
GAN-based Matrix Factorization for Recommender Systems
Proposed in 2014, Generative Adversarial Networks (GAN) initiated a fres...
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01/05/2022
An Evaluation Study of Generative Adversarial Networks for Collaborative Filtering
This work explores the reproducibility of CFGAN. CFGAN and its family of...
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10/11/2021
Feature Selection for Recommender Systems with Quantum Computing
The promise of quantum computing to open new unexplored possibilities in...
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05/14/2021
Measuring the User Satisfaction in a Recommendation Interface with Multiple Carousels
It is common for video-on-demand and music streaming services to adopt a...
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05/13/2021
A Methodology for the Offline Evaluation of Recommender Systems in a User Interface with Multiple Carousels
Many video-on-demand and music streaming services provide the user with ...
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04/12/2021
On the instability of embeddings for recommender systems: the case of Matrix Factorization
Most state-of-the-art top-N collaborative recommender systems work by le...
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08/03/2020
ContentWise Impressions: An Industrial Dataset with Impressions Included
In this article, we introduce the ContentWise Impressions dataset, a col...
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07/23/2020
Critically Examining the Claimed Value of Convolutions over User-Item Embedding Maps for Recommender Systems
In recent years, algorithm research in the area of recommender systems h...
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05/06/2020
A Collaborative Filtering Approach for the Automatic Tuning of Compiler Optimisations
Selecting the right compiler optimisations has a severe impact on progra...
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05/06/2020
A Collaborative Filtering Approah for the Automatic Tuning of Compiler Optimisations
Selecting the right compiler optimisations has a severe impact on progra...
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04/28/2020
Introducing a framework to assess newly created questions with Natural Language Processing
Statistical models such as those derived from Item Response Theory (IRT)...
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01/21/2020
R2DE: a NLP approach to estimating IRT parameters of newly generated questions
The main objective of exams consists in performing an assessment of stud...
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11/18/2019
A Troubling Analysis of Reproducibility and Progress in Recommender Systems Research
The design of algorithms that generate personalized ranked item lists is...
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08/29/2019
Towards Evaluating User Profiling Methods Based on Explicit Ratings on Item Features
In order to improve the accuracy of recommendations, many recommender sy...
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07/16/2019
Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approaches
Deep learning techniques have become the method of choice for researcher...
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02/25/2019
A Virtual Teaching Assistant for Personalized Learning
In this extended abstract, we propose an intelligent system that can be ...
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11/05/2018
Deriving item features relevance from collaborative domain knowledge
An Item based recommender system works by computing a similarity between...
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08/31/2018
A novel graph-based model for hybrid recommendations in cold-start scenarios
Cold-start is a very common and still open problem in the Recommender Sy...
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08/31/2018
Eigenvalue analogy for confidence estimation in item-based recommender systems
Item-item collaborative filtering (CF) models are a well known and studi...
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02/23/2018
Sequence-Aware Recommender Systems
Recommender systems are one of the most successful applications of data ...
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01/16/2018
Social Network based Short-Term Stock Trading System
This paper proposes a novel adaptive algorithm for the automated short-t...
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04/20/2017
Using Mise-En-Scène Visual Features based on MPEG-7 and Deep Learning for Movie Recommendation
Item features play an important role in movie recommender systems, where...
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07/30/2016