Organic search comprises a large portion of the total traffic for e-comm...
In this paper, based on the developed nonlinear fourth-order operator an...
In the relatively short history of machine learning, the subtle balance
...
The interventional nature of recommendation has attracted increasing
att...
The recent work by Rendle et al. (2020), based on empirical observations...
Selecting the optimal recommender via online exploration-exploitation is...
With the increasing scale of search engine marketing, designing an effic...
Sequential deep learning models such as RNN, causal CNN and attention
me...
The recent paper by Byrd Lipton (2019), based on empirical observati...
Product embeddings have been heavily investigated in the past few years,...
The feedback data of recommender systems are often subject to what was
e...
Tensor regression models, such as CP regression and Tucker regression, h...
Inductive representation learning on temporal graphs is an important ste...
Sequential modelling with self-attention has achieved cutting edge
perfo...
In this paper, we propose a new product knowledge graph (PKG) embedding
...
Modeling item complementariness and user preferences from purchase data ...
Modeling generative process of growing graphs has wide applications in s...