Name
Abstract | ||
|---|---|---|
Link streams model the dynamics of interactions in complex distributed systems as sequences of links (interactions) occurring at a given time. Detecting patterns in such sequences is crucial for many applications but it raises several challenges. In particular, there is no generic approach for the specification and detection of link stream patterns in a way similar to regular expressions and automata for text patterns. To address this, we propose a novel automata framework integrating both timed constraints and finite memory together with a recognition algorithm. The algorithm uses structures similar to tokens in high-level Petri nets and includes non-determinism and concurrency. We illustrate the use of our framework in real-world cases and evaluate its practical performances. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.7561/SACS.2018.2.161 | SCIENTIFIC ANNALS OF COMPUTER SCIENCE |
Keywords | Field | DocType |
Timed pattern recognition, difference bound matrices, finite-memory automata, timed automata, complex networks, link streams | Computer science,Automaton,Theoretical computer science,STREAMS,Pattern matching | Journal |
Volume | Issue | ISSN |
28 | 2 | 1843-8121 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Clément Bertrand | 1 | 0 | 0.68 |
| Frédéric Peschanski | 2 | 47 | 11.12 |
| Hanna Klaudel | 3 | 300 | 36.69 |
| Matthieu Latapy | 4 | 1488 | 103.74 |