@inproceedings{8e1a1d2ce6ad478e91be89b2977925af,
title = "ECOQUG: An effective ensemble community scoring function",
abstract = "A reasonable and effective community scoring function is of great significance since it can measure the community quality of groups we found more properly and help us discover more valuable communities. In this paper, we propose a new community scoring function, ECOQUG. Different from the existing community scoring functions, ECOQUG is designed based on the experimental study and theoretical analysis of groups with different community qualities. ECOQUG is more convincing. In addition, we design a series of experiments to examine the effectiveness and accuracy of ECOQUG and 13 other classic community scoring functions comprehensively. The extensive experimental results show that ECOQUG is effective and better than other community scoring functions.",
keywords = "Community quality, Community scoring function, Ground-truth communities, Network communities",
author = "Chunnan Wang and Hongzhi Wang and Chang Zhou and Jianzhong Li and Hong Gao",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 35th IEEE International Conference on Data Engineering, ICDE 2019 ; Conference date: 08-04-2019 Through 11-04-2019",
year = "2019",
month = apr,
doi = "10.1109/ICDE.2019.00177",
language = "英语",
series = "Proceedings - International Conference on Data Engineering",
publisher = "IEEE Computer Society",
pages = "1702--1705",
booktitle = "Proceedings - 2019 IEEE 35th International Conference on Data Engineering, ICDE 2019",
address = "美国",
}