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International Journal of Interactive Multimedia and Artificial Intelligence, 2023 Explanations in recommender systems are a requirement to improve users’ trust and experience. Traditionally, explanations in recommender systems are derived from their internal data regarding ratings, item features, and user profiles.
Marta Caro Martínez +2 more
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Hands on Explainable Recommender Systems with Knowledge Graphs
, 2022 The goal of this tutorial is to present the RecSys community with recent advances on explainable recommender systems with knowledge graphs. We will first introduce conceptual foundations, by surveying the state of the art and describing real-world ...
Fenu G. +3 more
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Digital Health, 2019 Objective Tailored digital health programs can promote positive health-related lifestyle changes and have been shown to be (cost) effective in trials. However, such programs are used suboptimally.
Kei Long Cheung +3 more
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Typology of personalization in recommender systems [PDF]
مدیریت نوآوری و راهبردهای عملیاتی, 2022 Purpose: With the development of science and technology, large volumes of structured, semi-structured, and unstructured data are generated daily at breakneck speeds from various sources.
Marziyeh Nourahmadi, Hojjatollah Sadeqi
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Capturing knowledge of user preferences with recommender systems [PDF]
, 2003 Capturing user preferences is a problematic task. Simply asking the users what they want is too intrusive and prone to error, yet monitoring behaviour unobtrusively and finding meaningful patterns is both difficult and computationally time consuming ...
Middleton, Stuart Edward +2 more
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Improving electronic customers' profile in recommender systems using data mining techniques [PDF]
Management Science Letters, 2011 Recommender systems are tools for realization one to one marketing. Recommender systems are systems, which attract, retain, and develop customers. Recommender systems use several ways to make recommendations.
Mohammad Julashokri +3 more
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Controllable Many-Objective Optimization for Fairness-Aware Uplift Modeling in Recommender Systems
IEEE AccessThis paper investigates the distribution of promotional offers under simultaneous budget, fairness, and treatment overlap constraints, using causal uplift modeling to estimate the incremental impact on personalized platforms and, specifically ...
Sunday O. Oladejo
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The transformative power of recommender systems in enhancing citizens’ satisfaction: Evidence from the Moroccan public sector [PDF]
Innovative MarketingThe study aims to specifically evaluate the potential impact of implementing AI-powered recommender systems on citizen satisfaction within Moroccan public services.
Ouissale El Gharbaoui +2 more
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A Scalable, Accurate Hybrid Recommender System
, 2010 Recommender systems apply machine learning techniques for filtering unseen information and can predict whether a user would like a given resource. There are three main types of recommender systems: collaborative filtering, content-based filtering, and ...
M.A. Ghazanfar +3 more
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Recommender Systems Evaluator: A Framework for Evaluating the Performance of Recommender Systems [PDF]
, 2021 Recommender systems are filters that suggest products of interest to customers, which may positively impact sales. Nowadays, there is a multitude of algorithms for recommender systems, and their performance varies widely.
Tardiole Kuehne, Bruno +13 more
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