Name
Abstract | ||
|---|---|---|
Pattern matching on a set of similar texts has received much attention, especially recently, mainly due to its application in cataloguing human genetic variation. In particular, many different algorithms have been proposed for the off-line version of this problem; that is, constructing a compressed index for a set of similar texts in order to answer pattern matching queries efficiently. However, the on-line, more fundamental, version of this problem is a rather undeveloped topic. Solutions to the on-line version can be beneficial for a number of reasons; for instance, efficient on-line solutions can be used in combination with partial indexes as practical trade-offs. We make here an attempt to close this gap via proposing two efficient algorithms for this problem. Notably, one of the algorithms requires time linear in the size of the textsu0027 representation, for short patterns. Furthermore, experimental results confirm our theoretical findings in practical terms. |
Year | Venue | Field |
|---|---|---|
2017 | CPM | Discrete mathematics,Computer science,Theoretical computer science,Pattern matching |
DocType | Citations | PageRank |
Conference | 2 | 0.41 |
References | Authors | |
0 | 9 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Roberto Grossi | 1 | 581 | 57.47 |
| Costas S. Iliopoulos | 2 | 1534 | 167.43 |
| Chang Liu | 3 | 571 | 117.41 |
| Nadia Pisanti | 4 | 302 | 30.91 |
| Solon P. Pissis | 5 | 281 | 57.09 |
| Ahmad Retha | 6 | 2 | 0.41 |
| Giovanna Rosone | 7 | 193 | 21.77 |
| Fatima Vayani | 8 | 25 | 3.85 |
| Luca Versari | 9 | 25 | 7.40 |