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A Neural Influence Diffusion Model for Social Recommendation
[article]
2019
arXiv
pre-print
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In this paper, we propose a deep influence propagation model to stimulate how users are influenced by the recursive social diffusion process for social recommendation. ...
We argue that, for each user of a social platform, her potential embedding is influenced by her trusted users. ...
CONCLUSIONS In this paper, we proposed a DiffNet neural model for social recommendation. ...
arXiv:1904.10322v1
fatcat:hyo2gnvjznejheoc63hojpor3q
DiffNet++: A Neural Influence and Interest Diffusion Network for Social Recommendation
[article]
2021
arXiv
pre-print
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Recently, we propose a preliminary work of a neural influence diffusion network (i.e., DiffNet) for social recommendation (Diffnet), which models the recursive social diffusion process to capture the higher-order ...
In this paper, we propose DiffNet++, an improved algorithm of DiffNet that models the neural influence diffusion and interest diffusion in a unified framework. ...
CONCLUSIONS AND FUTURE WORK In this paper, we presented a neural social and interest diffusion based model, i.e., DiffNet++, for social recommendation. ...
arXiv:2002.00844v4
fatcat:c3ru4lxozfef7hovzgwojrxqt4
SocialGCN: An Efficient Graph Convolutional Network based Model for Social Recommendation
[article]
2019
arXiv
pre-print
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2018 pre-print arXiv:1811.02815v1 fatcat:jwv6c322sferjj3mbyqn5o2ca4
To this end, in this paper, we propose an effective graph convolutional neural network based model for social recommendation. ...
Based on a classical CF model, the key idea of our proposed model is that we borrow the strengths of GCNs to capture how users' preferences are influenced by the social diffusion process in social networks ...
Model Architecture In this part, we build a SocialGCN model that depicts the influence of propagation on social networks for social recommendation. ...
arXiv:1811.02815v2
fatcat:rg7ak7rywfbjxlljcfdrdcvhsa
A New Supervised Epidemic Model for Intelligent Viral Content Classification
2016
International Journal of Intelligent Systems and Applications in Engineering
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The outputs of the proposed model are shown to be useful for the provenance problem and the diffusion prediction systems in both physical and social networks. ...
We collected epidemically diffused data from Twitter with supervision to create a ranking system that forms the base of our diffusion model. ...
Yang, Jaewon, and Jure Leskovec developed a Linear Influence Model that predicts global influence of a node in the network on the rate of diffusion. ...
doi:10.18201/ijisae.2016specialissue-146977
fatcat:faceb3vucneyrie4s5xbyrcilm
A Survey on Accuracy-oriented Neural Recommendation: From Collaborative Filtering to Information-rich Recommendation
[article]
2021
arXiv
pre-print
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In this survey paper, we conduct a systematic review on neural recommender models from the perspective of recommendation modeling with the accuracy goal, aiming to summarize this field to facilitate researchers ...
Influenced by the great success of deep learning in computer vision and language understanding, research in recommendation has shifted to inventing new recommender models based on neural networks. ...
For instance, DiffNet++ is proposed to jointly model the interest diffusion from user-item bipartite graph and the influence diffusion from the user-user social graph for user modeling in social recommendation ...
arXiv:2104.13030v3
fatcat:7bzwaxcarrgbhe36teik2rhl6e
Step Out of Your Comfort Zone: More Inclusive Content Recommendation for Networked Systems
[article]
2021
arXiv
pre-print
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To counteract the bias, we will consider information dissemination across network as a metric to assess the recommendation for contents e.g. new connections and news feed. ...
One crucial task on the social network is to recommend new content based on special characteristics of the graph structure. ...
And the influence diffusion layer models the dynamic diffusion process for the user's latent preference. ...
arXiv:2106.10408v1
fatcat:tccfan6a6zgmthfciwg2q3lrmm
Hierarchical Social Recommendation Model Based on a Graph Neural Network
2021
Wireless Communications and Mobile Computing
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Therefore, integrating social information into recommendation systems is of profound importance. We present an efficient network model for social recommendation. ...
With the continuous accumulation of social network data, social recommendation has become a widely used recommendation method. ...
DiffNet [44] is a hierarchical influence propagation structure for the simulation of the recursive dynamic diffusion process in social recommendations. ...
doi:10.1155/2021/9107718
fatcat:s4ovvdloyjgfdi7wwvvytfbox4
DyDiff-VAE: A Dynamic Variational Framework for Information Diffusion Prediction
[article]
2021
arXiv
pre-print
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This paper describes a novel diffusion model, DyDiff-VAE, for information diffusion prediction on social media. ...
Moreover, it has the lowest run-time compared with recurrent neural network based models. ...
the dynamic adjcency matrix and node attributes, and predicts the link existence. • GraphRec [6]: a novel graph neural network framework for social recommendations, which coherently models interactions ...
arXiv:2106.03251v1
fatcat:forh47cfcnhb3dlk44wq4mqr2u
Who is next: rising star prediction via diffusion of user interest in social networks
[article]
2022
arXiv
pre-print
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To address above challenges, in this paper, we observe that the presence of rising stars is closely correlated with the early diffusion of user interest in social networks, which is validated in the case ...
Thus, we propose a novel framework, RiseNet, to incorporate the user interest diffusion process with the item dynamic features to effectively predict rising stars. ...
More specifically, we first calculate two weights respectively: item attention for modeling dynamic item information's influence; and relationship attention for modeling user relationship' influence. ...
arXiv:2203.14807v2
fatcat:ah4i5bdct5hxfdzqvjazh5ce2u
Social Recommendation System Based on Hypergraph Attention Network
2021
Computational Intelligence and Neuroscience
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We propose a model that applies the hypergraph attention network to the social recommendation system (HASRE) to solve this problem. ...
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 ...
DiffNet++ [11] models influence diffusion and interest diffusion of neural networks in a unified framework based on DiffNet [12] . ...
doi:10.1155/2021/7716214
fatcat:mkbbpptjmrhetesyajq3vxpj4e
Dual Side Deep Context-aware Modulation for Social Recommendation
[article]
2021
arXiv
pre-print
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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 recommendation is effective in improving the recommendation performance by leveraging social relations from online social networking platforms. ...
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
Knowledge-aware Coupled Graph Neural Network for Social Recommendation
[article]
2021
arXiv
pre-print
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While many recent efforts show the effectiveness of neural network-based social recommender systems, several important challenges have not been well addressed yet: (i) The majority of models only consider ...
To tackle the above challenges, this work proposes a Knowledge-aware Coupled Graph Neural Network (KCGN) that jointly injects the inter-dependent knowledge across items and users into the recommendation ...
Acknowledgments We thank the anonymous reviewers for their constructive feedback and comments. ...
arXiv:2110.03987v1
fatcat:ra6xspadufe5dfjgntb5mfxlli
Discovering influencers for marketing in the blogosphere
2011
Information Sciences
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Introduction With the advent of online social networking, word-of-mouth (or viral) marketing is increasingly being recognized as a crucial strategy in social influence and marketing domains. ...
recommendations to their friends [32] . ...
The MATLAB neural network toolbox is applied to construct a three-layer ANN for training and testing the appropriate neural network model. ...
doi:10.1016/j.ins.2011.07.023
fatcat:chhwpkmycbauhp4fcjwnz63fei
Information Cascades Prediction With Graph Attention
2021
Frontiers in Physics
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Then, for temporal feature, a recurrent neural network is built to learn their structural context in several different time intervals based on timestamp with a time-decay attention. ...
To that end, in this paper, we propose a recurrent neural network model with graph attention mechanism, which constructs a seq2seq framework to learn the spatial-temporal cascade features. ...
[35] proposed to a social recommendation via a dynamic graph method. They encoded the long-short term preferences for users in a session based on RNN. ...
doi:10.3389/fphy.2021.739202
fatcat:i372tbbuw5h2hgoxptenkvj6ym
Identifying bloggers with marketing influence in the blogosphere
2009
Proceedings of the 11th International Conference on Electronic Commerce - ICEC '09
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Finding influential bloggers will not only allow us to better understand interesting activities happening in a social network, but also present unique opportunities for sales and advertisements. ...
In this paper, we address a novel problem of finding influential bloggers with marketing value in the blogosphere by proposing a MIV (Marketing Influential Value) model. ...
Back-propagation Neural Network Artificial neural network (ANN) is a model which is utilize mathematical or computational model based on biological neural networks. ...
doi:10.1145/1593254.1593307
dblp:conf/ACMicec/LiLC09
fatcat:mbbml7nahjalllijbl3w6mimiq
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