1. 华南理工大学经济与贸易学院,广东,广州,510006
2. 广州番禺职业技术学院信息工程学院,广东,广州,511483
3. 华南理工大学经济与贸易学院,广东,广州,510006
4. 广州番禺职业技术学院信息工程学院,广东,广州,511483
纸质出版:2017
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黄晓宇, 曾青松, 杨磊. Beta在线匹配[J]. 电子学报, 2017,45(5):1268-1271.
HUANG Xiao-yu, ZENG Qing-song, YANG Lei. Beta Online Matching[J]. Acta Electronica Sinica, 2017, 45(5): 1268-1271.
黄晓宇, 曾青松, 杨磊. Beta在线匹配[J]. 电子学报, 2017,45(5):1268-1271. DOI: 10.3969/j.issn.0372-2112.2017.05.033.
HUANG Xiao-yu, ZENG Qing-song, YANG Lei. Beta Online Matching[J]. Acta Electronica Sinica, 2017, 45(5): 1268-1271. DOI: 10.3969/j.issn.0372-2112.2017.05.033.
二部图的在线匹配问题最早由Karp等人在1990年提出,该问题在近年得到了广泛的关注,在日常生活中有大量的应用.本文引入了
Beta
分布作为二部图节点间的邻接关系的统计先验,提出了最大化节点的预留匹配能力准则作为在线匹配策略的评价度量,设计了在线匹配算法
Beta
OM,并证明了该算法的正确性.本文把
Beta
OM分别应用于基于人造数据和真实数据的在线匹配问题,实验的结果显示该算法优于经典的Greedy算法和Ranking算法.
In recent years
the online bipartite graph matching problem has attracted substantial research attention as many real-life problems can be eventually reduced to it.In this work
we study the classic online matching problem that was initially investigated by Karp in 1990.We adopt the
Beta
distribution as the prior distribution of the adjacency relation among the nodes
and present a novel measure to evaluate the matching policy.We also design
Beta
OM
a
Beta
distribution based online matching algorithm
and mathematically prove its soundness.Experiments with
Beta
OM as well as the benchmark algorithms on both synthetic and real data demonstrate that the proposed
Beta
OM is superior to the others.
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