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An Efficient Adaptive Attention Neural Network for Social Recommendation

Munan LI, Kenji Tei, Fukazawa Yoshiaki.
2020 IEEE Access  
Motivated by the above limitations, we designed a neural network model called adaptive attention neural network for social recommendation (ANSR) to study the interaction between a user and his or her social  ...  By utilizing the co-attention mechanism, we can not only extract the user's special attention to certain aspects of their friends but also determine the adaptive influences of different friends on the  ...  This paper proposed an efficient adaptive attention neural network for social recommendation (ANSR) model, which is a novel architecture based on a co-attention neural network.  ... 
doi:10.1109/access.2020.2984340 fatcat:enk5xziaarajlmmkl6hw6mz2ei

Propagation-aware Social Recommendation by Transfer Learning [article]

Haodong Chang, Yabo Chu
2021 arXiv   pre-print
for recommendation by an attention mechanism.  ...  In this paper, we propose a novel Propagation-aware Transfer Learning Network (PTLN) based on the propagation of social relations.  ...  Secondly, friends in the same order will have different importance for preference learning. We apply the attention mechanism to adaptively learn the importance of friends in the same order.  ... 
arXiv:2107.04846v1 fatcat:v5dkffhuzfepfjh42glc7w7lfi

Survey for Trust-aware Recommender Systems: A Deep Learning Perspective [article]

Manqing Dong, Feng Yuan, Lina Yao, Xianzhi Wang, Xiwei Xu, Liming Zhu
2020 arXiv   pre-print
This survey provides a systemic summary of three categories of trust-aware recommender systems: social-aware recommender systems that leverage users' social relationships; robust recommender systems that  ...  A significant remaining challenge for existing recommender systems is that users may not trust the recommender systems for either lack of explanation or inaccurate recommendation results.  ...  Rafailidis and Weiss [77] propose a similar structure that considers a subset of friends and uses an attention mechanism for social collaborative filtering.  ... 
arXiv:2004.03774v2 fatcat:q7mehir7hbbzpemw3q5fkby5ty

Dual Side Deep Context-aware Modulation for Social Recommendation [article]

Bairan Fu and Wenming Zhang and Guangneng Hu and Xinyu Dai and Shujian Huang and Jiajun Chen
2021 arXiv   pre-print
Specifically, we first proposed a novel graph neural network to model the social relation and collaborative relation, and on top of high-order relations, a dual side deep context-aware modulation is introduced  ...  Social relations among users provide friends' information for modeling users' interest in candidate items and help items expose to potential consumers (i.e., item attraction).  ...  ACKNOWLEDGMENTS We want to express gratitude to the anonymous reviewers for their hard work. This work is funded by NSFC 61976114 and NSFC 61936012.  ... 
arXiv:2103.08976v1 fatcat:svlxdyqawjcadpgwnai2enwkji

Recent Advances in Heterogeneous Relation Learning for Recommendation [article]

Chao Huang
2021 arXiv   pre-print
We discuss the learning approaches in each category, such as matrix factorization, attention mechanism and graph neural networks, for effectively distilling heterogeneous contextual information.  ...  In this survey, we review the development of recommendation frameworks with the focus on heterogeneous relational learning, which consists of different types of dependencies among users and items.  ...  Additionally, with the introduction of attention mechanism, an adaptive transfer learning scheme is designed to model the interplay between user and item domain for social recommendation [Chen et al  ... 
arXiv:2110.03455v1 fatcat:fskj4qdsibfnxefklazdli3tgu

DAN-SNR: A Deep Attentive Network for Social-Aware Next Point-of-Interest Recommendation [article]

Liwei Huang, Yutao Ma, Yanbo Liu, Keqing He
2020 arXiv   pre-print
In particular, the DAN-SNR makes use of the self-attention mechanism instead of the architecture of recurrent neural networks to model sequential influence and social influence in a unified manner.  ...  In this study, we discuss a new topic of next POI recommendation and present a deep attentive network for social-aware next POI recommendation called DAN-SNR.  ...  Ma is the corresponding author of this paper.  ... 
arXiv:2004.12161v1 fatcat:7ymnb4z4kndbrfkjwy35sy67aq

SocialTrans: A Deep Sequential Model with Social Information for Web-Scale Recommendation Systems [article]

Qiaoan Chen, Hao Gu, Lingling Yi, Yishi Lin, Peng He, Chuan Chen, Yangqiu Song
2020 arXiv   pre-print
In this paper, we present a novel deep learning model SocialTrans for social recommendations to integrate these two types of preferences. SocialTrans is composed of three modules.  ...  The second module is a multi-layer graph attention neural network (GAT), which is used to model the social influence strengths between friends in social networks.  ...  Socially influenced preference is captured by a graph attention neural network without considering edge attributes and the multihead attention mechanism.  ... 
arXiv:2005.04361v1 fatcat:m4gsis6p7faajkhtf5u76ok3om

Modelling High-Order Social Relations for Item Recommendation [article]

Yang Liu, Liang Chen, Xiangnan He, Jiaying Peng, Zibin Zheng, Jie Tang
2020 arXiv   pre-print
The high-order social relations, e.g., the friends of friends, which very informative to reveal user preference, have been largely ignored.  ...  Distinct from mainstream social recommenders that regularize the model learning with social relations, we instead propose to directly factor social relations in the predictive model, aiming at learning  ...  To address the second challenge of varying importance, we design an neural attention mechanism to adaptively aggregate the user embeddings learned by different layers.  ... 
arXiv:2003.10149v1 fatcat:276lcg3qiveh5ehgwhtvvwz2jy

Social Recommendation System Based on Hypergraph Attention Network

Zhongxiu Xia, Weiyu Zhang, Ziqiang Weng, Syed Hassan Ahmed
2021 Computational Intelligence and Neuroscience  
However, because the influence of the users' friends is different, we use the graph attention mechanism to capture the users' attention to different friends and adaptively model selection information for  ...  We propose a model that applies the hypergraph attention network to the social recommendation system (HASRE) to solve this problem.  ...  ) SBPR [44] : SBPR uses social relations as a more accurate ranking-based model, by assuming that users tend to assign higher rankings to items that their friends prefer. (3) LightGCN [45] : LightGCN  ... 
doi:10.1155/2021/7716214 fatcat:mkbbpptjmrhetesyajq3vxpj4e

Spatio-Temporal Attention based Recurrent Neural Network for Next Location Prediction

Basmah Altaf, Lu Yu, Xiangliang Zhang
2018 2018 IEEE International Conference on Big Data (Big Data)  
In this work, we design a novel model to enforce contextual constraints on sequential data by designing a spatial and temporal attention mechanisms over recurrent neural network that leverages the importance  ...  Attention mechanism helps us to learn which POIs bounded by time difference and spatial distance in user checkin history are important for the prediction of next POI.  ...  ACKNOWLEDGMENT This work is supported by King Abdullah University of Science and Technology (KAUST), Saudi Arabia.  ... 
doi:10.1109/bigdata.2018.8622218 dblp:conf/bigdataconf/AltafYZ18 fatcat:vz7mgveg7zcwnfouwt7x3eoaha

A Survey on Deep Learning Based Point-Of-Interest (POI) Recommendations [article]

Md. Ashraful Islam, Mir Mahathir Mohammad, Sarkar Snigdha Sarathi Das, Mohammed Eunus Ali
2020 arXiv   pre-print
for a user.  ...  Location-based Social Networks (LBSNs) enable users to socialize with friends and acquaintances by sharing their check-ins, opinions, photos, and reviews.  ...  [39] proposed Adaptive Sequence Partitioner with Power-law Attention (ASPPA) model to learn the latent structures of the check-in sequences.  ... 
arXiv:2011.10187v1 fatcat:3uampnqerfdvnpuzrxcrsjviwq

Recommendation system using a deep learning and graph analysis approach [article]

Mahdi Kherad, Amir Jalaly Bidgoly
2021 arXiv   pre-print
When a user connects to the Internet to fulfill his needs, he often encounters a huge amount of related information.  ...  The advances in machine learning methods, especially deep learning, have led to great achievements in recommender systems, although these systems still suffer from challenges such as cold-start and sparsity  ...  , and present a new model of social MF based on adaptive trust network training to accurately reflect social relationships.  ... 
arXiv:2004.08100v8 fatcat:olpgxe5u5zg3tphqbofgdfilmu

Research Commentary on Recommendations with Side Information: A Survey and Research Directions [article]

Zhu Sun, Qing Guo, Jie Yang, Hui Fang, Guibing Guo, Jie Zhang, Robin Burke
2019 arXiv   pre-print
One involves the different methodologies of recommendation: the memory-based methods, latent factor, representation learning, and deep learning models.  ...  To address these issues, a great number of recommendation algorithms have been proposed to leverage side information of users or items (e.g., social network and item category), demonstrating a high degree  ...  We also gratefully acknowledge the support of National Natural Science Foundation of China (Grant No. 71601104, 71601116, 71771141 and 61702084) and the support of the Fundamental Research Funds for the  ... 
arXiv:1909.12807v2 fatcat:2nj4crzcd5attidhd3kneszmki

Hybrid Deep Neural Networks for Friend Recommendations in Edge Computing Environment

Jibing Gong, Hao Peng, Bowen Du, Yi Zhao, Shuai Chen, Hongfei Wang, Linfeng Du, Shuli Wang, Jianhua Li, Md Zakirul Alam Bhuiyan, Mingsheng Liu
2019 IEEE Access  
Meanwhile, with the advent of deep learning, it has become more challenging to integrate these features into a deep neural network framework for friend recommendation.  ...  In this paper, we propose DFRec++, a hybrid deep neural network framework combining attribute attention and network embeddings to make social friend recommendations with the help of both interactive semantics  ...  For example, if one of the hobbies of a user is traveling, he or she might prefer to become friends with another travel enthusiast.  ... 
doi:10.1109/access.2019.2958599 fatcat:cerq7vbyyrcuxhrt7heqhpby4e

Textually Guided Ranking Network for Attentional Image Retweet Modeling [article]

Zhou Zhao, Hanbing Zhan, Lingtao Meng, Jun Xiao, Jun Yu, Min Yang, Fei Wu, Deng Cai
2018 arXiv   pre-print
We then develop a novel attentional multi-faceted ranking network learning framework with textually guided multi-modal neural networks for the proposed heterogenous IRM network to learn the joint image  ...  Unlike previous studies, we learn user preference ranking model from their past retweeted image tweets in SMS.  ...  We thus employ attention mechanism [13] to adaptively incorporate users' followee preference for jointly predicting targeted user's image retweet behavior.  ... 
arXiv:1810.10226v1 fatcat:w6gvlba6gbhn5mdmkmbs5i4mcm
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