Results 11 to 20 of about 5,774 (216)
Towards Cognitive Recommender Systems
Algorithms, 2020 Intelligence is the ability to learn from experience and use domain experts’ knowledge to adapt to new situations. In this context, an intelligent Recommender System should be able to learn from domain experts’ knowledge and experience, as it is vital to
Amin Beheshti +5 more
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Embedding Based Recommender systems, a review and comparison. [PDF]
The Egyptian Journal of Language Engineering, 2022 This paper provides a summary and review of embedding based recommender systems. Word embedding frameworks like word2vec were originally developed for NLP tasks.
Ahmed Ragab, Passant El-Kafrawy
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Food recommender systems for diabetic patients: a narrative review [PDF]
Reviews in Clinical Medicine, 2017 World Health Organization (WHO) estimates that the number of people with diabetes will grow 114% by 2030. It declares that patients themselves have more responsibility for controlling and the treatment of diabetes by being provided with updated knowledge
Somaye Norouzi +4 more
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Recommender Systems in the Real Estate Market—A Survey
Applied Sciences, 2021 The shift to e-commerce has changed many business areas. Real estate is one of the applications that has been affected by this modern technological wave. Recommender systems are intelligent models that assist users of real estate platforms in finding the
Alireza Gharahighehi +2 more
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Assessment Methods for Evaluation of Recommender Systems: A Survey
Foundations of Computing and Decision Sciences, 2021 The recommender system (RS) filters out important information from a large pool of dynamically generated information to set some important decisions in terms of some recommendations according to the user’s past behavior, preferences, and interests.
Kuanr Madhusree, Mohapatra Puspanjali
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Promoting cold-start items in recommender systems. [PDF]
PLoS ONE, 2014 As one of the major challenges, cold-start problem plagues nearly all recommender systems. In particular, new items will be overlooked, impeding the development of new products online.
Jin-Hu Liu +5 more
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IEEE Access, 2021 With the ever-growing volume of online information, recommender system has been an effective strategy to overcome such information overload. Recommender systems are widely used in many web applications, such as e-commerce, news, agriculture and other ...
Caixia Song, Haoyu Dong
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Optimization of Recommender Systems Using Particle Swarms
Ingeniería, 2023 Background: Recommender systems are one of the most widely used technologies by electronic businesses and internet applications as part of their strategies to improve customer experiences and boost sales.
Nancy Yaneth Gelvez Garcia +2 more
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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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Users’ Responsiveness to Persuasive Techniques in Recommender Systems
Frontiers in Artificial Intelligence, 2021 Understanding user’s behavior and their interactions with artificial-intelligent-based systems is as important as analyzing the performance of the algorithms used in these systems.
Alaa Alslaity, Thomas Tran
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