Name
Abstract | ||
|---|---|---|
A temporal graph is a graph in which vertices communicate with each other at specific time, e.g., A calls B at 11 a.m. and talks for 7 minutes, which is modeled by an edge from A to B with starting time “11 a.m.” and duration “7 mins”. Temporal graphs can be used to model many networks with time-related activities, but efficient algorithms for analyzing temporal graphs are severely inadequate. We study fundamental problems such as answering reachability and time-based path queries in a temporal graph, and propose an efficient indexing technique specifically designed for processing these queries in a temporal graph. Our results show that our method is efficient and scalable in both index construction and query processing. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/ICDE.2016.7498236 | 2016 IEEE 32nd International Conference on Data Engineering (ICDE) |
Keywords | Field | DocType |
reachability query,path query,temporal graph,indexing technique,query processing,index construction | Query optimization,Graph,Query language,Vertex (geometry),Information retrieval,Computer science,Search engine indexing,Theoretical computer science,Reachability,Database,Scalability | Conference |
ISSN | Citations | PageRank |
1084-4627 | 10 | 0.51 |
References | Authors | |
38 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Huanhuan Wu | 1 | 32 | 3.93 |
| Yuzhen Huang | 2 | 10 | 0.51 |
| James Cheng | 3 | 2044 | 101.89 |
| Jinfeng Li | 4 | 24 | 2.14 |
| Yiping Ke | 5 | 1056 | 46.24 |