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Neural Collaborative with Sentence BERT for News Recommender System

Budi Juarto, Abba Suganda Girsang
2021 JOIV: International Journal on Informatics Visualization  
Neural collaborative filtering is usually being used for recommendation systems by combining collaborative filtering with neural networks.  ...  The recommendation system can make it easier for users to choose the news to read. The method that can be used in providing recommendations from the same user is collaborative filtering.  ...  Content-based filtering provides new recommendations based on content in providing recommendations. For example, there are titles, categories, and news content in the news.  ... 
doi:10.30630/joiv.5.4.678 fatcat:gaboovym3rax3h5js2cod25nxa

Comparative study on traditional recommender systems and deep learning based recommender systems

N.L. Anantha, Bhanu Bathula
2018 Advances in Modelling and Analysis B  
Recommender systems is a big breakthrough for the field of e-commerce. Product recommendation is challenging task to e-commerce companies.  ...  In this paper performance of Traditional Recommender Systems and Deep Learning-based Recommender Systems are compared.  ...  Recommender Systems are categorized into mainly 3 types 1) Content based filtering 2) Collaborative filtering 3) Knowledge-based Systems. The content in Content Based filtering means descriptions.  ... 
doi:10.18280/ama_b.610202 fatcat:4iur3pjuujdkha6dyt3v6ntequ

Use of Deep Learning in Modern Recommendation System: A Summary of Recent Works

Ayush Singhal, Pradeep Sinha, Rakesh Pant
2017 International Journal of Computer Applications  
for recommendation.  ...  We organize the review in three parts: Collaborative system, Content based system and Hybrid system.  ...  This stage of news recommendation is a step before final news recommendation for end users.  ... 
doi:10.5120/ijca2017916055 fatcat:m6icpquumbgczhrdnya7x35of4

Deep Learning-Based Recommendation: Current Issues and Challenges

Rim Fakhfakh, Anis Ben, Chokri Ben
2017 International Journal of Advanced Computer Science and Applications  
Then we finish by presenting the recommendation approach adopted by the most popular video recommendation platform YouTube which is based essentially on deep learning advances.  ...  In this paper, we provide a recent literature review of researches dealing with deep learning based recommendation approaches which is preceded by a presentation of the main lines of the recommendation  ...  Challenges and Current Issues The collaborative filtering and the content based filtering models are commonly used for recommendation.  ... 
doi:10.14569/ijacsa.2017.081209 fatcat:lj5udwsfwfezxkwp5y7i44ruly

MovieANN: Film Öneri Sistemlerine Çok Katmanlı Yapay Sinir Ağı Kullanarak Karma Bir Yaklaşım

Sait Can Yücebaş
2019 Çanakkale Onsekiz Mart Üniversitesi Fen Bilimleri Enstitüsü Dergisi  
These systems are based on collaborative filtering, content based filtering and hybrid approaches.  ...  We combined collaborative and contentbased filtering to build a hybrid movie recommendation system, MovieANN, based on neural network model.  ...  Collaborative filtering generalizes the preferences of the similar users. Thus, recommendation is easy for a new user when compared to content based filtering.  ... 
doi:10.28979/comufbed.597093 fatcat:bxsczv3elbfdbj5i2hwiux4t54

User Demographic Information and Deep Neural Network in Film Recommendation System based on Collaborative Filtering

Adrianus Lunardi Pradana, Computer Science Department, BINUS Graduate Program – Master of Computer Science Bina Nusantara University, Jakarta, Indonesia 11480, Antoni Wibowo
2022 International Journal of Emerging Technology and Advanced Engineering  
Keywords — collaborative filtering, deep neural network, demographic information, neural collaborative filtering, recommendation system  ...  One of the major problems in deep neural network based collaborative filtering recommendation system was coldstart problem.  ...  Other research shows that neural collaborative filtering can also be used for news recommender system with additional help from sentence BERT [15] and gender debiased career and college major recommendation  ... 
doi:10.46338/ijetae0522_16 fatcat:gfc5nm6cavgbhnb6xnujacgghm

A Study of Neural Network Learning-Based Recommender System

Sumi Shin
2017 The International Journal of Engineering and Science  
This study proposes a neural network learning model as a new technique to find neighboring users using the collaborative filtering method.  ...  In particular, collaborative filtering (CF) is the most widely used technique in these recommendation systems.  ...  Recommendation techniques include collaborative filtering, content-based filtering and demographic filtering.  ... 
doi:10.9790/1813-0601038486 fatcat:qq3xupqpmvewbarzoadyv2yl4q

A Hybrid Latent Variable Neural Network Model for Item Recommendation [article]

Michael R. Smith, Tony Martinez, Michael Gashler
2014 arXiv   pre-print
LNN outperforms a broad selection of content-based filters (which make recommendations based on item descriptions) and other hybrid approaches while maintaining the accuracy of state-of-the-art collaborative  ...  In this paper, we present a neural network model with latent input variables (latent neural network or LNN) as a hybrid collaborative filtering technique that addresses the cold-start problem.  ...  Two commonly used classes of recommender systems are content-based filters and collaborative filters.  ... 
arXiv:1406.2235v1 fatcat:mocr4cycvbc4vggqyerfp36cra

Content-Aware Collaborative Music Recommendation Using Pre-Trained Neural Networks

Dawen Liang, Minshu Zhan, Daniel P. W. Ellis
2015 Zenodo  
ACKNOWLEDGEMENTS We gratefully acknowledge the support of NVIDIA Corporation with the donation of the Tesla K40 GPU used for this research. REFERENCES [1] Thierry Bertin-Mahieux, Daniel P.W.  ...  CONCLUSION In this paper we present a content-aware collaborative music recommendation system that joins a multi-layer neural network content model with a collaborative filtering model.  ...  Two primary approaches exist in recommendation: collaborative filtering and content-based methods.  ... 
doi:10.5281/zenodo.1416308 fatcat:grpfm3xuefhllhc5lv6kmpxdly

An Application-oriented Review of Deep Learning in Recommender Systems

Jyoti Shokeen, Chhavi Rana
2019 International Journal of Intelligent Systems and Applications  
Recommender systems have been proved helpful in choosing relevant items. Several algorithms for recommender systems have been proposed in previous years.  ...  This paper gives a brief overview of various deep learning techniques and their implementation in recommender systems for various applications.  ...  Traditional algorithms for designing RSs are mainly of three types: collaborative filtering, content-based filtering and hybrid algorithms.  ... 
doi:10.5815/ijisa.2019.05.06 fatcat:67fgexfbfjh2no5b3phvohbole

Content Filtering Enriched GNN Framework for News Recommendation [article]

Yong Gao, Huifeng Guo, Dandan Lin, Yingxue Zhang, Ruiming Tang, Xiuqiang He
2021 arXiv   pre-print
It is compatible with existing GNN-based approaches for news recommendation and can capture both collaborative and content filtering information simultaneously.  ...  In this paper, to address such limitations, we propose content filtering enriched GNN framework for news recommendation, ConFRec in short.  ...  The proposed framework improves the recommendation performance by fully considering both collaborative and content filtering information, and is compatible with existing GNN-based approaches for news recommendation  ... 
arXiv:2110.12681v1 fatcat:ryu33qdjwvhg3jn7s5rnq4eyt4

A Hybrid Recommender System for Recommending Smartphones to Prospective Customers [article]

Pratik K. Biswas, Songlin Liu
2021 arXiv   pre-print
Some hybrid recommender systems have combined collaborative filtering and content-based approaches to build systems that are more robust.  ...  In essence, we use the outputs from ALS (collaborative filtering) to influence the recommendations from a Deep Neural Network (DNN), which combines characteristic, contextual, structural and sequential  ...  A variety of techniques has been proposed over the years for performing recommendations, including collaborative filtering, content-based filtering, demographic filtering, etc.  ... 
arXiv:2105.12876v1 fatcat:6q3wpnmkerd7pnnpsfhvbilxca

Deep Learning Innovations in Recommender Systems

Bilal Ahmed, Li Wang, Muhammad Amjad, Waqar Hussain, Syed Badar-ud-Duja, M. Abdul
2019 International Journal of Computer Applications  
These deep recommender systems can be used to understand the demands of users and improve the value in recommendations.  ...  In this study we provide an overview of traditional approaches their limitations and then discuss about the aspects of deep learning used in the recommender system domain to improve the accuracy in recommender  ...  A typical scenario is to apply content based statistics of a new item without the user rate in the collaborative filtering recommender systems [5] .  ... 
doi:10.5120/ijca2019918882 fatcat:tuhfyyytkzbifc74ewqjgcs5wq

A Review for Recommender System Models and Deep Learning

F. Nagy, A. Haroun, Hatem Abdel-Kader, Arabi Keshk
2021 IJCI. International Journal of Computers and Information  
In this paper we introduce an overview for the traditional recommendation systems models, the recommendation systems advantages and shortcoming, the recommendation systems challenges, common deep learning  ...  traditional technology, how deep learning-based recommendation systems works, deep learning for recommendations and open problems and the novel research trends on this field.  ...  Collaborative Filtering Content Based filtering Hybrid filtering Number of users VI.  ... 
doi:10.21608/ijci.2021.207864 fatcat:hdwzp3o4djcsdo6ubqfkdmu3o4

Improvement of e-commerce recommendation systems with deep hybrid collaborative filtering with content: A case study

Filip Wójcik, Michał Górnik
2020 Econometrics  
This paper presents a proposition to utilize flexible neural network architecture called Deep Hybrid Collaborative Filtering with Content (DHCF) as a product recommendation engine.  ...  The system was tested on 2018 Amazon Reviews Dataset, using repeated cross validation and compared with other approaches: collaborative filtering (CF) and deep collaborative filtering (DCF) in terms of  ...  As technology and processing power evolved, new ideas for solving the problem emerged -ranging from matrix decomposition, through collaborative filtering, to neural networks.  ... 
doi:10.15611/eada.2020.3.03 fatcat:efkdsujufnbrjbinns7oe4cxt4
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