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VisMatchmaker: Cooperation of the User and the Computer in Centralized Matching Adjustment

Authors Law, Po Ming HKUST affiliated (currently or previously)
Wu, Wenchao HKUST affiliated (currently or previously)
Zheng, Yixian HKUST affiliated (currently or previously)
Qu, Huamin View this author's profile
Issue Date 2017
Source IEEE Transactions on Visualization and Computer Graphics , v. 23, (1), January 2017, article number 7539560, p. 231-240
Summary Centralized matching is a ubiquitous resource allocation problem. In a centralized matching problem, each agent has a preference list ranking the other agents and a central planner is responsible for matching the agents manually or with an algorithm. While algorithms can find a matching which optimizes some performance metrics, they are used as a black box and preclude the central planner from applying his domain knowledge to find a matching which aligns better with the user tasks. Furthermore, the existing matching visualization techniques (i.e. bipartite graph and adjacency matrix) fail in helping the central planner understand the differences between matchings. In this paper, we present VisMatchmaker, a visualization system which allows the central planner to explore alternatives to an algorithm-generated matching. We identified three common tasks in the process of matching adjustment: problem detection, matching recommendation and matching evaluation. We classified matching comparison into three levels and designed visualization techniques for them, including the number line view and the stacked graph view. Two types of algorithmic support, namely direct assignment and range search, and their interactive operations are also provided to enable the user to apply his domain knowledge in matching adjustment. © 2016 IEEE.
ISSN 1077-2626
Language English
Format Article
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