Name
Abstract | ||
|---|---|---|
Graph databases witness the rise of Graph Query Language (GQL) in recent years, which enables non-programmers to express a graph query. However, the current solution does not support motif-related queries on knowledge graphs, which are proven important in many real-world scenarios. In this paper, we propose a GQL framework for mining knowledge graphs, named M-Cypher. It supports motif-related graph queries in an effective, efficient and user-friendly manner. We demonstrate the usage of the system by the emerging Covid-19 knowledge graph analytic tasks.
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Year | DOI | Venue |
|---|---|---|
2020 | 10.1145/3340531.3417440 | CIKM '20: The 29th ACM International Conference on Information and Knowledge Management
Virtual Event
Ireland
October, 2020 |
DocType | ISBN | Citations |
Conference | 978-1-4503-6859-9 | 0 |
PageRank | References | Authors |
0.34 | 6 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiaodong Li | 1 | 0 | 0.68 |
| Reynold Cheng | 2 | 3069 | 154.13 |
| Matin Najafi | 3 | 0 | 0.34 |
| Kevin Chang | 4 | 355 | 21.42 |
| Xiaolin Han | 5 | 0 | 0.34 |
| Hongtai Cao | 6 | 1 | 1.03 |