A Fused Forensic Text Comparison System Using Lexical Features, Word and Character N-grams A Likelihood Ratio-based Analysis in Predatory Chatlog Messages
This study investigates the degree that the performance of a likelihood ratio (LR)-based forensic text comparison (FTC) system improves by using logistic-regression fusion on LRs that were separately estimated by three different procedures, involving lexical features, word-based N-grams and character-based N-grams. This study uses predatory chatlog messages. The number of words used for modelling each group of messages is 500 words. The performance of the FTC system is assessed in terms of its...[Show more]
|Collections||ANU Research Publications|
|Source:||Proceedings of 2014 International Conference on Advances in Computing,Communications and Informatics (ICACCI)|
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