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Multi-objective optimization with recommender systems: A systematic review
Recommender systems have become essential in modern information systems and Internet
applications by delivering personalized and pertinent content to users. While conventional …
applications by delivering personalized and pertinent content to users. While conventional …
Recommender systems for sustainability: overview and research issues
Sustainability development goals (SDGs) are regarded as a universal call to action with the
overall objectives of planet protection, ending of poverty, and ensuring peace and prosperity …
overall objectives of planet protection, ending of poverty, and ensuring peace and prosperity …
Sports recommender systems: overview and research directions
Sports recommender systems receive an increasing attention due to their potential of
fostering healthy living, improving personal well-being, and increasing performances in …
fostering healthy living, improving personal well-being, and increasing performances in …
Exploring the added effect of three recommender system techniques in mobile health interventions for physical activity: a longitudinal randomized controlled trial
Physical inactivity is a public health issue. Mobile health interventions to promote physical
activity often still experience dropout, resulting in people not adhering to the interventions …
activity often still experience dropout, resulting in people not adhering to the interventions …
A multi-population based evolutionary algorithm for many-objective recommendations
L Zhang, H Zhang, Z Chen, S Liu… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Multi-objective evolutionary algorithms (MOEAs) have been proved to be competitive in
recommender systems. As the application scenarios of recommender systems become …
recommender systems. As the application scenarios of recommender systems become …
Precision-Driven Product Recommendation Software: Unsupervised Models, Evaluated by GPT-4 LLM for Enhanced Recommender Systems
This paper presents a pioneering methodology for refining product recommender systems,
introducing a synergistic integration of unsupervised models—K-means clustering, content …
introducing a synergistic integration of unsupervised models—K-means clustering, content …
Evolutionary approach for building, exploring and recommending complex items with application in nutritional interventions
Over the last few years, the ability of recommender systems to help us in different
environments has been increasing. Several systems try to offer solutions in highly complex …
environments has been increasing. Several systems try to offer solutions in highly complex …
Preference-learning emitters for mixed-initiative quality-diversity algorithms
In mixed-initiative cocreation tasks, wherein a human and a machine jointly create items, it is
important to provide multiple relevant suggestions to the designer. Quality-diversity …
important to provide multiple relevant suggestions to the designer. Quality-diversity …
Sports recommender systems: overview and research issues
Sports recommender systems receive an increasing attention due to their potential of
fostering healthy living, improving personal well-being, and increasing performances in …
fostering healthy living, improving personal well-being, and increasing performances in …
Connecting physical activity with context and motivation: a user study to define variables to integrate into mobile health recommenders
In this paper, we aim to improve existing health recommender systems by defining relevant
contextual and motivational variables to recommend physical activities and collect …
contextual and motivational variables to recommend physical activities and collect …