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The current recommender systems for research papers do not involve short-term and long-term models; they mostly use the whole user reading history. Hence, they ...
In this paper, we present a novel user modelling method for representing short-term and long-term user's interests in recommending research papers. The short- ...
Paper. A Novel Short-term and Long-term User Modelling Technique for a Research Paper Recommender System. Topics: User Profiling and Recommender Systems. In ...
A Novel Short-term and Long-term User Modelling Technique for a Research Paper Recommender System. M Al Alshaikh, G Uchyigit, R Evans. KDIR, 255-262, 2017. 2 ...
A novel short-term and long-term user modelling technique for a research paper recommender system. Al AlshaikhM. et al. Predicting future interests in a ...
In particular, the proposed model consists of a nonlocal network for long- term preference modeling and a geo-dilated RNN for short- term preference learning.
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A natural way to improve the recommender is to combine both long-term and short-term modeling. Previous approaches neglect the importance of dynamically ...
An attention-based framework to combine users' long-term and short-term preferences, thus users' representation can be generated adaptively according to the ...
work on modelling short and long term preferences in recommender systems. The rest of this paper is organized as follows. Section II presents the related work.
We propose an attention- based fusion method to adaptively incorporate the short- and long-term preferences under specific circumstances, such as when (if the ...