Generalizing identity-based string comparison metrics: Framework and techniques
作者:
Highlights:
•
摘要
In this paper, we propose a framework that aims at handling metrics among strings defined over heterogeneous alphabets. Furthermore, we illustrate in detail its application to generalize one of the most important string metrics, namely the edit distance. This last activity leads us to define the Multi-Parameterized Edit Distance (MPED). As for this last metric, we investigate its computational properties and solution algorithms, and we present several experiments for its evaluation. As a final contribution, we provide several notes about some possible applications of MPED and other generalized metrics in different scenarios.
论文关键词:String metrics,Generalized string similarity framework,Matching schema,Generalized metric function,Multi-parameterized edit distance
论文评审过程:Received 17 May 2018, Revised 25 June 2019, Accepted 26 June 2019, Available online 28 June 2019, Version of Record 18 November 2019.
论文官网地址:https://doi.org/10.1016/j.knosys.2019.06.028