Fitted Q-iteration and functional networks for ubiquitous recommender systems
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DOI: 10.1007/s00500-016-2248-1
Abstract: Ubiquitous recommender systems facilitate users on-location by personalized recommendations of items in the proximity via mobile devices. Due to a high variability of situations and preferences, an efficient resource processing is needed in order to… read more here.
Keywords: functional networks; recommender; ubiquitous recommender; fitted iteration ... See more keywords
A deep learning-based hybrid model for recommendation generation and ranking
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DOI: 10.1007/s00521-020-04844-4
Abstract: A recommender system plays a vital role in information filtering and retrieval, and its application is omnipresent in many domains. There are some drawbacks such as the cold-start and the data sparsity problems which affect… read more here.
Keywords: recommender; deep learning; model; learning based ... See more keywords
Neural embedding collaborative filtering for recommender systems
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DOI: 10.1007/s00521-020-04920-9
Abstract: The main purpose of collaborative filtering algorithm is to provide a personalized recommender system based on past interactions of each user (e.g., clicks and purchases). Among various collaborative filtering techniques, matrix factorization is widely adopted… read more here.
Keywords: collaborative filtering; recommender; neural embedding; matrix factorization ... See more keywords
Revisiting recommender systems: an investigative survey
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DOI: 10.1007/s00521-024-10828-5
Abstract: This paper provides a thorough review of recommendation methods from academic literature, offering a taxonomy that classifies recommender systems (RSs) into categories like collaborative filtering, content-based systems, and hybrid systems. It examines the effectiveness and… read more here.
Keywords: recommender; investigative survey; recommender systems; systems investigative ... See more keywords
Recommender systems in model-driven engineering
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DOI: 10.1007/s10270-021-00905-x
Abstract: Recommender systems are information filtering systems used in many online applications like music and video broadcasting and e-commerce platforms. They are also increasingly being applied to facilitate software engineering activities. Following this trend, we are… read more here.
Keywords: recommender; systems model; model driven; recommender systems ... See more keywords
An actor-critic based recommender system with context-aware user modeling
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DOI: 10.1007/s10462-025-11134-9
Abstract: Recommendation systems empower users with tailored service assistance by learning about their interactions with systems and recommending items based on their preferences and interests. Typical recommender systems view the recommendation process as a static procedure… read more here.
Keywords: recommender; based recommender; recommender system; context aware ... See more keywords
Wasserstein GAN-based architecture to generate collaborative filtering synthetic datasets
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DOI: 10.1007/s10489-024-05313-4
Abstract: Currently, generative applications are reshaping different fields, such as art, computer vision, speech processing, and natural language. The computer science personalization area is increasingly relevant since large companies such as Spotify, Netflix, TripAdvisor, Amazon, and… read more here.
Keywords: recommender; number; method; architecture ... See more keywords
Linguistics-based dialogue simulations to evaluate argumentative conversational recommender systems
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DOI: 10.1007/s11257-024-09403-3
Abstract: Conversational recommender systems aim at recommending the most relevant information for users based on textual or spoken dialogues, through which users can communicate their preferences to the system more efficiently. Argumentative conversational recommender systems represent… read more here.
Keywords: recommender; recommender systems; argumentative conversational; conversational recommender ... See more keywords
A Novel Clustering Algorithm in a Neutrosophic Recommender System for Medical Diagnosis
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DOI: 10.1007/s12559-017-9462-8
Abstract: Decision-making processes have been extensively used in artificial intelligence and cognitive sciences to explain and improve individual and social perception. As one of the most typical decision-making problems, medical diagnosis is used to analyze the… read more here.
Keywords: system; neutrosophic recommender; recommender; novel clustering ... See more keywords
Facilitating research through serendipity of recommendations
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DOI: 10.1007/s12652-019-01354-7
Abstract: Recommender systems are used to suggest items that are useful to users. The recommendations can be surprising and may be categorized as serendipitous recommendations. One of the limitations with serendipitous recommendations is that the user… read more here.
Keywords: recommender; recommender system; serendipity; serendipitous recommendations ... See more keywords
A hybrid recommender system for patron driven library acquisition and weeding
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DOI: 10.1016/j.jksuci.2020.10.017
Abstract: Abstract Nowadays the explosion of information sources has shaped how library users access information and provide feedback on their preferences. Therefore, faced with this explosion and the blossoming of digital libraries, modern libraries must take… read more here.
Keywords: recommender; acquisition weeding; recommender system; patron driven ... See more keywords