Name
Abstract | ||
|---|---|---|
This Demo presents G-Miner, a distributed system for graph mining. The take-aways for Demo attendees are: (1) a good understanding of the challenges of various graph mining workloads; (2) useful insights on how to design a good system for graph mining by comparing G-Miner with existing systems on performance, expressiveness and user-friendliness; and (3) how to use G-Miner for interactive graph analytics.
|
Year | DOI | Venue |
|---|---|---|
2019 | 10.1145/3299869.3320219 | Proceedings of the 2019 International Conference on Management of Data |
Keywords | Field | DocType |
distributed system, large-scale graph mining | Data mining,Graph,Computer science,Graph analytics,Expressivity | Conference |
ISSN | ISBN | Citations |
0730-8078 | 978-1-4503-5643-5 | 1 |
PageRank | References | Authors |
0.35 | 0 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hongzhi Chen | 1 | 47 | 13.00 |
| Xiaoxi Wang | 2 | 7 | 5.23 |
| Chenghuan Huang | 3 | 1 | 1.02 |
| Juncheng Fang | 4 | 1 | 0.68 |
| Yifan Hou | 5 | 6 | 1.79 |
| Changji Li | 6 | 2 | 1.37 |
| James Cheng | 7 | 2044 | 101.89 |