https://scholars.lib.ntu.edu.tw/handle/123456789/607258
標題: | Structure-aware parameter-free group query via heterogeneous information network transformer | 作者: | Chen H.-W Shuai H.-H Yang D.-N Lee W.-C Shi C Yu P.S MING-SYAN CHEN |
關鍵字: | Graph neural network;Group quer;HIN;Transformer;Social networking (online);Activity informations;Heterogeneous information;Learning Based Models;On-line social networks;Research communities;State-of-the-art methods;Structure-aware;Team formation;Information services | 公開日期: | 2021 | 卷: | 2021-April | 起(迄)頁: | 2075-2080 | 來源出版物: | Proceedings - International Conference on Data Engineering | 會議論文: | 37th IEEE International Conference on Data Engineering, ICDE 2021 | 摘要: | Owing to a wide range of important applications, such as team formation, dense subgraph discovery, and activity attendee suggestions on online social networks, Group Query attracts a lot of attention from the research community. However, most existing works are constrained by a unified social tightness k (e.g., for k-core, or k-plex), without considering the diverse preferences of social cohesiveness in individuals. In this paper, we introduce a new group query, namely Parameter-free Group Query (PGQ), and propose a learning-based model, called PGQN, to find a group that accommodates personalized requirements on social contexts and activity topics. First, PGQN extracts node features by a GNN-based method on Heterogeneous Activity Information Network (HAIN). Then, we transform the PGQ into a graph-to-set (Graph2Set) problem to learn the diverse user preference on topics and members, and find new attendees to the group. Experimental results manifest that our proposed model outperforms nine state-of-the-art methods by at least 51% in terms of F1-score on three public datasets. ? 2021 IEEE. |
URI: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85112868201&doi=10.1109%2fICDE51399.2021.00203&partnerID=40&md5=ad261f282a8a341345c865036f79bb09 https://scholars.lib.ntu.edu.tw/handle/123456789/607258 |
ISSN: | 10844627 | DOI: | 10.1109/ICDE51399.2021.00203 |
顯示於: | 電機工程學系 |
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