Time series forecasting (TSF) is fundamentally required in many real-wor...
Click-Through Rate (CTR) prediction is one of the core tasks in recommen...
Reranking is attracting incremental attention in the recommender systems...
Recommender systems play a vital role in modern online services, such as...
Recommender systems (RS) work effective at alleviating information overl...
A common challenge in personalized user preference prediction is the
col...
Modeling user interests is crucial in real-world recommender systems. In...
Commonsense knowledge is critical in human reading comprehension. While
...
Click-through rate (CTR) prediction is a critical task for many industri...
Personalized recommendation benefits users in accessing contents of inte...
Data sparsity is an inherent challenge in the recommender systems, where...
Recommender system (RS) devotes to predicting user preference to a given...
Recommender system (RS) has become crucial module in commercial systems....
Features play an important role in most prediction tasks of e-commerce
r...
Recently, interactive recommender systems are becoming increasingly popu...
This paper targets to a novel but practical recommendation problem named...
Deep learning based methods have been widely used in industrial
recommen...
Network embedding has proved extremely useful in a variety of network
an...
Ranking is a core task in E-commerce recommender systems, which aims at
...
Modeling users' dynamic and evolving preferences from their historical
b...
Existing recommendation algorithms mostly focus on optimizing traditiona...
Ranking is a fundamental and widely studied problem in scenarios such as...
In this paper, we study the product title summarization problem in E-com...
Tasks such as search and recommendation have become increas- ingly impor...
In web search, mutual influences between documents have been studied fro...
This paper studies the problem of automatically extracting a short title...
Slot filling is a critical task in natural language understanding (NLU) ...
Recurrent neural networks have achieved excellent performance in many
ap...
In the 'Big Data' era, many real-world applications like search involve ...