@inproceedings{f992821bf7fe4e45b44baa3f09e94e3e,
title = "Personalized top-n influential community search over large social networks",
abstract = "User-centered analysis is one of the aims of online community search. In this paper, we study personalized top-n influential community search that has a practical application. Given an evolving social network, where every edge has a propagation probability, we propose a maximal pk-Clique community model, that uses a new cohesive criterion. The criterion requires that the propagation probability of each edge or each maximal influence path between two vertices that is considered as an edge, is greater than p. The maximal clique problem is an NP-hard problem, and the introduction of this cohesive criterion makes things worse, as it may add new edges to existing networks. To conduct personalized top-n influential community search efficiently in such networks, we first introduce a search space refinement method. We then present pruning based and heuristic based search approaches. The proposed algorithms more than double the efficiency of the search performance for basic solutions. The effectiveness and efficiency of our algorithms have been verified using four real datasets.",
keywords = "Community search, Heuristic search, Online, Pruning",
author = "Jian Xu and Xiaoyi Fu and Liming Tu and Ming Luo and Ming Xu and Ning Zheng",
note = "Funding Information: Acknowledgment. This work is supported by the National Natural Science Foundation of China (No. 61572165), the Natural Science Foundation of Zhejiang Province (No. LZ15F 020003). Xiaoyi Fu{\textquoteright}s work is supported by Hong Kong Research Grants Council (No. 12200817, 12201615 and 12258116). Funding Information: This work is supported by the National Natural Science Foundation of China (No. 61572165), the Natural Science Foundation of Zhejiang Province (No. LZ15F 020003). Xiaoyi Fu{\textquoteright}s work is supported by Hong Kong Research Grants Council (No. 12200817, 12201615 and 12258116).; 2nd Asia Pacific Web and Web-Age Information Management Joint Conference on Web and Big Data, APWeb-WAIM 2018 ; Conference date: 23-07-2018 Through 25-07-2018",
year = "2018",
doi = "10.1007/978-3-319-96890-2_9",
language = "English",
isbn = "9783319968896",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "105--120",
editor = "Jianliang Xu and Yoshiharu Ishikawa and Yi Cai",
booktitle = "Web and Big Data - Second International Joint Conference, APWeb-WAIM 2018, Proceedings",
address = "Germany",
}