Name
Title | ||
|---|---|---|
A General Approach to Uniformly Handle Different String Metrics Based on Heterogeneous Alphabets. |
Abstract | ||
|---|---|---|
In the last few years, we have assisted in a great increase of the usage of strings in the most disparate areas. In the meantime, the development of the Internet has brought the necessity of managing strings from very different contexts and possibly using different alphabets. This issue is not addressed by the numerous string comparison metrics previously proposed in the literature. In this paper, we aim at providing a contribution in this context. In fact, first we propose an approach to measure the similarity of strings based on different alphabets. Then we show that our approach can be specifically adapted to several classic string comparison metrics and that each specialization can lead to addressing completely different issues. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/ACCESS.2020.2978893 | IEEE ACCESS |
Keywords | DocType | Volume |
Measurement,Pattern matching,Proteins,Computer science,Time series analysis,Internet,Bioinformatics,String metrics,generalized string similarity framework,edit distance,Jaccard distance | Journal | 8 |
ISSN | Citations | PageRank |
2169-3536 | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Francesco Cauteruccio | 1 | 0 | 0.68 |
| Alessandro Cucchiarelli | 2 | 226 | 36.38 |
| Christian Morbidoni | 3 | 289 | 37.76 |
| Giorgio Terracina | 4 | 701 | 70.85 |
| Domenico Ursino | 5 | 897 | 104.96 |