379 citations · 488 across the 11 of their papers we have counts for
11 papers
Enhanced Doubly Robust Learning for Debiasing Post-click Conversion Rate Estimation
Siyuan Guo, Lixin Zou, Yiding Liu +6
Post-click conversion, as a strong signal indicating the user preference, is salutary for building recommender systems. However, accurately estimating the post-click conversion rat…
Preference-driven Similarity Join
Chuancong Gao, Jiannan Wang, Jian Pei +2
Similarity join, which can find similar objects (e.g., products, names, addresses) across different sources, is powerful in dealing with variety in big data, especially web data. T…
Attributed Network Embedding for Learning in a Dynamic Environment
Jundong Li, Harsh Dani, Xia Hu +3
Network embedding leverages the node proximity manifested to learn a low-dimensional node vector representation for each node in the network. The learned embeddings could advance v…
Streaming Recommender Systems
Shiyu Chang, Yang Zhang, Jiliang Tang +4
The increasing popularity of real-world recommender systems produces data continuously and rapidly, and it becomes more realistic to study recommender systems under streaming scena…
Scaling Submodular Maximization via Pruned Submodularity Graphs
Tianyi Zhou, Hua Ouyang, Yi Chang +2
We propose a new random pruning method (called "submodular sparsification (SS)") to reduce the cost of submodular maximization. The pruning is applied via a "submodularity graph" o…
A Survey of Signed Network Mining in Social Media
Jiliang Tang, Yi Chang, Charu Aggarwal +1
Many real-world relations can be represented by signed networks with positive and negative links, as a result of which signed network analysis has attracted increasing attention fr…