Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10342429 | Digital Investigation | 2014 | 8 Pages |
Abstract
This work's contribution is to introduce automated approximate matching evaluation on real data by relating approximate matching results to the longest common substring (LCS). Specifically, we introduce a computationally efficient LCS approximation and use it to obtain ground truth on the t5 set. Using the results, we evaluate three existing approximate matching schemes relative to LCS and analyze their performance.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Networks and Communications
Authors
Frank Breitinger, Vassil Roussev,