Name
Abstract | ||
|---|---|---|
With the development of on-line social networks, more and more users and sellers are interested in group analytics which provides insights into common interests with various relationships. This paper addresses this problem from temporal aspect, i.e., temporal group query (TGQ) which gives people the historical view for group forming and changing. To efficiently achieve our goal, we propose two structures to index temporal social network (TSN), and then a simple naive searching method is designed to process the TGQ, after that we argue a more efficient approach can be implemented by update operations instead of iterative graph generations, which we call optimized method. We conduct experiments on real-synthetic dataset, and the results show that our indexes and searching algorithms are capable, and optimized method is much more efficient than the naive one. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/DEXA.2016.047 | 2016 27th International Workshop on Database and Expert Systems Applications (DEXA) |
Keywords | Field | DocType |
temporal social network,group query processing,online social networks,group analytics,temporal aspect,naive searching method,TSN,group changing,group forming,TGQ,temporal group query | Data mining,Graph,Search algorithm,Social network,Computer science,Iterative method,Search engine indexing,Theoretical computer science,Analytics,Database | Conference |
ISSN | ISBN | Citations |
1529-4188 | 978-1-5090-3636-3 | 0 |
PageRank | References | Authors |
0.34 | 6 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiaoying Chen | 1 | 8 | 3.26 |
| Chong Zhang | 2 | 8 | 4.95 |
| Yan-Li Hu | 3 | 17 | 2.55 |
| Bin Ge | 4 | 4 | 3.14 |
| Weidong Xiao | 5 | 8 | 3.60 |