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
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
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
Professional reviews as service: A mix method approach to assess the value of recommender systems in the entertainment industry
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DOI: 10.1016/j.techfore.2021.120800
Abstract: Abstract As a recommender system, Metacritic (metacritic.com) quantifies and aggregates reviews of entertainment products. The metascore published by Metacritic is controversial in its process for gathering, translating, and aggregating reviews. This study aims to assess… read more here.
Keywords: reviews service; recommender; professional reviews; entertainment industry ... See more keywords
User Heterogeneity and Individualized Recommender
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DOI: 10.1088/0256-307x/34/6/068902
Abstract: Previous works on personalized recommendation mostly emphasize modeling peoples' diversity in potential favorites into a uniform recommender. However, these recommenders always ignore the heterogeneity of users at an individual level. In this study, we propose… read more here.
Keywords: recommender; individualized recommender; heterogeneity individualized; user heterogeneity ... See more keywords
A Survey of Collaborative Filtering-Based Recommender Systems: From Traditional Methods to Hybrid Methods Based on Social Networks
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DOI: 10.1109/access.2018.2877208
Abstract: In the era of big data, recommender system (RS) has become an effective information filtering tool that alleviates information overload for Web users. Collaborative filtering (CF), as one of the most successful recommendation techniques, has… read more here.
Keywords: collaborative filtering; recommendation; based recommendation; information ... See more keywords
Evaluating Collaborative Filtering Recommender Algorithms: A Survey
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DOI: 10.1109/access.2018.2883742
Abstract: Due to the explosion of available information on the Internet, the need for effective means of accessing and processing them has become vital for everyone. Recommender systems have been developed to help users to find… read more here.
Keywords: recommendation; algorithms; recommender; evaluation metrics ... See more keywords