Jan 9, 2021 · This paper proposed a deep learning based algorithm for multi-criteria recommender systems, which captures the non-linear and non-trivial user– ...
A novel deep hybrid recommender system based on auto-encoder with neural collaborative filtering ... Big Data Min. Anal. 2018.
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We propose in this article a novel sentiment DL based algorithm for multi-criteria recommendation using autoencoders and sentiment information. Two ...
A Deep Learning Based Approach for Context-Aware Multi-Criteria ...
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Deep multi-criteria collaborative filtering (DMCCF) model [11] - A benchmark for MCRS that employs deep learning and multi-criteria in recommendation systems. 2 ...
A deep learning based algorithm for multi-criteria recommender systems · Qusai Y. Shambour ; Deep learning techniques for rating prediction: a survey of the ...
Sep 30, 2023 · An autoencoder-based deep learning model for solving the sparsity issues of Multi-Criteria Recommender System · CoDFi-DL: a hybrid recommender ...
Jun 1, 2022 · We apply deep neural network (DNN) models to predict the context-aware multi-criteria ratings and learn the aggregation function. We conduct ...
Oct 19, 2023 · [43] conducted a systematic review of neural recommender models, categorizing them based on data usage into collaborative filtering, content- ...
Our approach exploits non-linear interpretative recommendations by exploring Multi-criteria ratings by combination of Autoencoders with dropout layer and ...
As a remedy, multi-criteria recommender systems (MCRSs) have emerged as an alternative paradigm, allowing users to rate items based on multiple dimensions. The ...