An effect of background population sample size on the performance of a likelihood ratio-based forensic text comparison system: A Monte Carlo simulation with Gaussian mixture model
This is a Monte Carlo simulation-based study that explores the effect of the sample size of the background database on a likelihood ratio (LR)-based forensic text comparison (FTC) system built on multivariate authorship attribution features. The text messages written by 240 authors who were randomly selected from an archive of chatlog messages were used in this study. The strength of evidence (= LR) was estimated using the multivariate kernel density likelihood ratio (MVKD) formula with a...[Show more]
|Collections||ANU Research Publications|
|Source:||Proceedings of Australasian Language Technology Association Workshop 2016 Workshop|
|Access Rights:||Open Access|
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