20 citations · 25 across the 5 of their papers we have counts for
7 papers
A General Early-Stopping Module for Crowdsourced Ranking
Caihua Shan, Leong Hou U, Nikos Mamoulis +2
Crowdsourcing can be used to determine a total order for an object set (e.g., the top-10 NBA players) based on crowd opinions. This ranking problem is often decomposed into a set o…
An End-to-End Deep RL Framework for Task Arrangement in Crowdsourcing Platforms
Caihua Shan, Nikos Mamoulis, Reynold Cheng +3
In this paper, we propose a Deep Reinforcement Learning (RL) framework for task arrangement, which is a critical problem for the success of crowdsourcing platforms. Previous works…
Efficient Algorithms for Densest Subgraph Discovery
Yixiang Fang, Kaiqiang Yu, Reynold Cheng +2
Densest subgraph discovery (DSD) is a fundamental problem in graph mining. It has been studied for decades, and is widely used in various areas, including network science, biologic…
A Survey of Community Search Over Big Graphs
Yixiang Fang, Xin Huang, Lu Qin +4
With the rapid development of information technologies, various big graphs are prevalent in many real applications (e.g., social media and knowledge bases). An important component…
Detecting Data Errors with Statistical Constraints
Jing Nathan Yan, Oliver Schulte, Jiannan Wang +1
A powerful approach to detecting erroneous data is to check which potentially dirty data records are incompatible with a user's domain knowledge. Previous approaches allow the user…
Exploring Communities in Large Profiled Graphs
Yankai Chen, Yixiang Fang, Reynold Cheng +3
Given a graph and a vertex , the community search (CS) problem aims to efficiently find a subgraph of whose vertices are closely related to . Communities are pre…