11 citations · 17 across the 5 of their papers we have counts for
5 papers
Rethinking Multi-objective Ranking Ensemble in Recommender System: From Score Fusion to Rank Consistency
Boyang Xia, Zhou Yu, Zhiliang Zhu +5
The industrial recommender systems always pursue more than one business goals. The inherent intensions between objectives pose significant challenges for ranking stage. A popular s…
Privileged Features Distillation at Taobao Recommendations
Chen Xu, Quan Li, Junfeng Ge +7
Features play an important role in the prediction tasks of e-commerce recommendations. To guarantee the consistency of off-line training and on-line serving, we usually utilize the…
Personalized Re-ranking for Recommendation
Changhua Pei, Yi Zhang, Yongfeng Zhang +6
Ranking is a core task in recommender systems, which aims at providing an ordered list of items to users. Typically, a ranking function is learned from the labeled dataset to optim…
Multi-Source Pointer Network for Product Title Summarization
Fei Sun, Peng Jiang, Hanxiao Sun +3
In this paper, we study the product title summarization problem in E-commerce applications for display on mobile devices. Comparing with conventional sentence summarization, produc…
Combination of Diverse Ranking Models for Personalized Expedia Hotel Searches
Xudong Liu, Bing Xu, Yuyu Zhang +5
The ICDM Challenge 2013 is to apply machine learning to the problem of hotel ranking, aiming to maximize purchases according to given hotel characteristics, location attractiveness…