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Collaborative Deep Learning for Recommender Systems [article]

Hao Wang and Naiyan Wang and Dit-Yan Yeung
2015 arXiv   pre-print
Collaborative filtering (CF) is a successful approach commonly used by many recommender systems.  ...  (CF-based) input and propose in this paper a hierarchical Bayesian model called collaborative deep learning (CDL), which jointly performs deep representation learning for the content information and collaborative  ...  This calls for integrating deep learning with CF by performing deep learning collaboratively. Unfortunately, very few attempts have been made to develop deep learning models for CF.  ... 
arXiv:1409.2944v2 fatcat:ehe27qx3sjf2rnyqko6ynyeeg4

Collaborative Deep Learning for Recommender Systems

Hao Wang, Naiyan Wang, Dit-Yan Yeung
2015 Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining - KDD '15  
Collaborative filtering (CF) is a successful approach commonly used by many recommender systems.  ...  (CF-based) input and propose in this paper a hierarchical Bayesian model called collaborative deep learning (CDL), which jointly performs deep representation learning for the content information and collaborative  ...  This calls for integrating deep learning with CF by performing deep learning collaboratively. Unfortunately, very few attempts have been made to develop deep learning models for CF.  ... 
doi:10.1145/2783258.2783273 dblp:conf/kdd/WangWY15 fatcat:wdwrvnrqyzczxi3a5dken6y5dm

Collaborative Deep Forest Learning for Recommender Systems

Soheila Molaei, Amirhossein Havvaei, Hadi Zare, Mahdi Jalili
2021 IEEE Access  
INDEX TERMS Recommender systems, social networks, deep learning, collaborative filtering, representational learning.  ...  Collaborative filtering (CF) is one of the most practical approaches on recommendation systems by predicting users' preferences for items based on the user-item interaction information.  ...  LITERATURE REVIEW Data sparsity is a critical problem in recommender systems for collaborative filtering (CF) techniques, particularly for new users and items.  ... 
doi:10.1109/access.2021.3054818 fatcat:gvyjzdcgbna37l2mb5pzyy65yu

Deep Learning Architecture for Collaborative Filtering Recommender Systems

Jesus Bobadilla, Santiago Alonso, Antonio Hernando
2020 Applied Sciences  
This paper provides an innovative deep learning architecture to improve collaborative filtering results in recommender systems.  ...  We use the deep learning architecture to extract the existing non-linear relations between predictions, reliabilities, and accurate recommendations.  ...  Please note that the proposed method acts as a collaborative filtering black box that is fed just with the votes of each Recommender System.  ... 
doi:10.3390/app10072441 fatcat:rahpirobifc2fiip7qv3ocgopy

An Efficient Deep Learning Approach for Collaborative Filtering Recommender System

Mohammed Fadhel Aljunid, Manjaiah Dh
2020 Procedia Computer Science  
In this work, we propose a deep learning method of collaborative recommender systems (DLCRS). We have made a comparative study of the proposed method and existing methods.  ...  In this work, we propose a deep learning method of collaborative recommender systems (DLCRS). We have made a comparative study of the proposed method and existing methods.  ...  Proposed Methodology In this section, we introduce an efficient deep learning approach for collaborative recommender system.  ... 
doi:10.1016/j.procs.2020.04.090 fatcat:3sinlqz6bjcyhkyel4jkksu4ia

Multi-model deep learning approach for collaborative filtering recommendation system

Mohammed Fadhel Aljunid, Manjaiah Doddaghatta Huchaiah
2020 CAAI Transactions on Intelligence Technology  
Though implicit feedback is too challenging, it is highly applicable to use in building recommendation systems.  ...  As a result of a huge volume of implicit feedback such as browsing and clicks, many researchers are involving in designing recommender systems (RSs) based on implicit feedback.  ...  Recently, the application of deep learning is achieving remarkable successes in the area of collaborative filtering [39] , which is considered to be the first work to apply deep learning approach.  ... 
doi:10.1049/trit.2020.0031 fatcat:ss4anwktjreopajttixq4chdde

Collaborative filtering and deep learning based recommendation system for cold start items

Jian Wei, Jianhua He, Kai Chen, Yi Zhou, Zuoyin Tang
2017 Expert systems with applications  
The experiment results on Netflix movie recommendation show the tight coupling of CF approach and deep learning neural network is feasible and very effective for cold start item recommendation.  ...  In this paper, we propose two recommendation models to solve the CCS and ICS problems for new items, which are based on a framework of tightly coupled CF approach and deep learning neural network.  ...  Collaborative deep learning (CDL) is a representative example that applies deep learning to recommendation systems by integrating stacked denoising autoencoder (SDAE) into a simple latent factor based  ... 
doi:10.1016/j.eswa.2016.09.040 fatcat:eqp2ttybybabtiamzm6u5sfhg4

PHD: A Probabilistic Model of Hybrid Deep Collaborative Filtering for Recommender Systems

Jie Liu, Dong Wang, Yue Ding
2017 Asian Conference on Machine Learning  
Collaborative Filtering (CF), a well-known approach in producing recommender systems, has achieved wide use and excellent performance not only in research but also in industry.  ...  Extensive experiments for four datasets demonstrate that our proposed model outperforms other traditional approaches and deep learning models making it state of the art.  ...  As for part of future work, we will think about how to reduce the fine-tuning time in deep learning models with recommender systems.  ... 
dblp:conf/acml/LiuWD17 fatcat:io3feeih25gxlkrwz6ynyctbay

Service Recommendations with Deep Learning: A Study on Neural Collaborative Engines

Pasquale De Rosa, Michel Deriaz, Marco De Marco, Luigi Laura
2022 Pacific Asia Journal of the Association for Information Systems  
The present paper aims to investigate the adoption of Neural Networks for recommendation systems and to propose Deep Learning architectures as advanced frameworks for designing Collaborative Filtering  ...  Results: The results of this study demonstrate the primary role of Feed-Forward Neural Networks for designing advanced Collaborative recommenders, consolidating and even improving the outcomes of the work  ...  Introduction This paper investigates the suitability of a Deep-Learning-based approach for designing advanced collaborative recommendation systems.  ... 
dblp:journals/pajais/RosaDML22 fatcat:dchbq6srfrh37ctqfa7vfp7pk4

Neural Autoregressive Collaborative Filtering for Implicit Feedback

Yin Zheng, Cailiang Liu, Bangsheng Tang, Hanning Zhou
2016 Proceedings of the 1st Workshop on Deep Learning for Recommender Systems - DLRS 2016  
This paper proposes implicit CF-NADE, a neural autoregressive model for collaborative filtering tasks using implicit feedback ( e.g. click, watch, browse behaviors).  ...  Acknowledgements We thank Hugo Larochelle and the reviewers for many helpful discussions.  ...  CF lies at the core of most recommender systems and has attracted increasing attention along with the recent boom of e-commerce and social network systems.  ... 
doi:10.1145/2988450.2988453 dblp:conf/recsys/ZhengLTZ16 fatcat:m6ig6pyygfgtlb4jot5wd2ccda

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.  ...  The review concludes by discussion of the impact of deep learning in recommendation system in various domain and whether deep learning has shown any significant improvement over the conventional systems  ...  a deep learning based architecture for hybrid recommendation system.  ... 
doi:10.5120/ijca2017916055 fatcat:m6icpquumbgczhrdnya7x35of4

RECOMMENDER SYSTEMS BASED ON DEEP LEARNING

Xushbaqov Sherzod, Khamraev Mansur, Bakhtiyorova Mokhiruy
2022 Zenodo  
Then, the details of deep learning-based collaborative filtering recommender systems are provided.  ...  Next, we present deep learning-based hybrid recommender systems and deep learning in social network-based recommender systems. Finally, we describe deep learning in contextaware recommender systems.  ...  Deep learning in collaborative filtering recommender systems Collaborative filtering (CF) is a widely used approach in recommender systems to solve many real world problems.  ... 
doi:10.5281/zenodo.6473945 fatcat:kwzv2uc25ngjzg5sxver7yp2ke

A Survey of State-of-the-art: Deep Learning Methods on Recommender System

Basiliyos Tilahun, Charles Awono, Bernabe Batchakui
2017 International Journal of Computer Applications  
In this paper different traditional recommendation techniques, deep learning approaches for recommender system and survey of deep learning techniques on recommender system are presented.  ...  Due to the limitation of the traditional recommendation methods in obtaining accurate result a deep learning approach is introduced both for collaborative and content based approaches that will enable  ...  SURVEY OF DEEP LEARNING TECHNIQUES ON RECOMMENDER SYSTEM Deep learning has recently been proposed in building a recommender systems both for collaborative and content based approaches [10, 40] .  ... 
doi:10.5120/ijca2017913361 fatcat:txeaquy5dfdelezsly4g7ze3ca

An Application-oriented Review of Deep Learning in Recommender Systems

Jyoti Shokeen, Chhavi Rana
2019 International Journal of Intelligent Systems and Applications  
This paper gives a brief overview of various deep learning techniques and their implementation in recommender systems for various applications.  ...  The increasing research in recommender systems using deep learning proves the success of deep learning techniques over traditional methods of recommender systems.  ...  Deep collaborative filtering has also been tested for movie recommendation [37] . [29] have proposed a collaborative deep learning model that uses deep learning to retrieve the textual information and  ... 
doi:10.5815/ijisa.2019.05.06 fatcat:67fgexfbfjh2no5b3phvohbole

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

N.L. Anantha, Bhanu Bathula
2018 Advances in Modelling and Analysis B  
Deep Learning techniques in the field of Recommender Systems can be directly applied. Deep Learning has ample number of algorithms.  ...  In this paper performance of Traditional Recommender Systems and Deep Learning-based Recommender Systems are compared.  ...  Deep learning is also showing remarkable impact on the Recommender Systems. Deep learning techniques consists of activation functions and uses Neural Networks.  ... 
doi:10.18280/ama_b.610202 fatcat:4iur3pjuujdkha6dyt3v6ntequ
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