scholarly journals Transfer-Meta Framework for Cross-domain Recommendation to Cold-Start Users

Author(s):  
Yongchun Zhu ◽  
Kaikai Ge ◽  
Fuzhen Zhuang ◽  
Ruobing Xie ◽  
Dongbo Xi ◽  
...  
Keyword(s):  
2020 ◽  
Vol 1 ◽  
pp. 194-206
Author(s):  
Hanxin Wang ◽  
Daichi Amagata ◽  
Takuya Makeawa ◽  
Takahiro Hara ◽  
Niu Hao ◽  
...  

Author(s):  
Wenjing Fu ◽  
Zhaohui Peng ◽  
Senzhang Wang ◽  
Yang Xu ◽  
Jin Li

As one promising way to solve the challenging issues of data sparsity and cold start in recommender systems, crossdomain recommendation has gained increasing research interest recently. Cross-domain recommendation aims to improve the recommendation performance by means of transferring explicit or implicit feedback from the auxiliary domain to the target domain. Although the side information of review texts and item contents has been proven to be useful in recommendation, most existing works only use one kind of side information and cannot deeply fuse this side information with ratings. In this paper, we propose a Review and Content based Deep Fusion Model named RC-DFM for crossdomain recommendation. We first extend Stacked Denoising Autoencoders (SDAE) to effectively fuse review texts and item contents with the rating matrix in both auxiliary and target domains. Through this way, the learned latent factors of users and items in both domains preserve more semantic information for recommendation. Then we utilize a multi-layer perceptron to transfer user latent factors between the two domains to address the data sparsity and cold start issues. Experimental results on real datasets demonstrate the superior performance of RC-DFM compared with state-of-the-art recommendation methods.Deeply Fusing Reviews and Contents for Cold Start Users in Cross-Domain Recommendation Systems


Author(s):  
Ignacio Fernández-Tobías ◽  
Paolo Tomeo ◽  
Iván Cantador ◽  
Tommaso Di Noia ◽  
Eugenio Di Sciascio
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Author(s):  
Sander Ruben Aarten

AbstractSince the introduction of India’s cold start and Pakistan’s full spectrum deterrence doctrines, the subcontinental deterrence landscape has been characterised by strong cross-domain dynamics. In extremis, if both states adhere to the threats issued in their doctrines a Pakistan-supported militant attack on Indian soil could escalate into an all-out nuclear exchange. It is a development that has been met with great concern by many analysts for its detrimental impact on deterrence stability. Since the doctrines are believed to have become operational, at least four incidents occurred which could have sparked this cross-domain escalation spiral. And yet, crisis behaviour proved vastly different from what doctrine predicted. What does this say about deterrence stability on the subcontinent? This chapter assesses deterrence stability on the basis of perfect deterrence theory, which is argued to provide a more nuanced view of deterrence relationships than classical deterrence theory. It finds support for the stability-instability paradox and argues that deterrence is less unstable than appears at first sight. Furthermore, to fully appreciate the degree of deterrence stability, it is suggested that the factors ‘context’ and ‘narrative’ should be included into the equation.


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