The Influence of Background Data Size on the Performance of a Score-based Likelihood Ratio System: A Case of Forensic Text Comparison

Shunichi Ishihara


Abstract
This study investigates the robustness and stability of a likelihood ratio–based (LR-based) forensic text comparison (FTC) system against the size of background population data. Focus is centred on a score-based approach for estimating authorship LRs. Each document is represented with a bag-of-words model, and the Cosine distance is used as the score-generating function. A set of population data that differed in the number of scores was synthesised 20 times using the Monte-Carol simulation technique. The FTC system’s performance with different population sizes was evaluated by a gradient metric of the log–LR cost (Cllr). The experimental results revealed two outcomes: 1) that the score-based approach is rather robust against a small population size—in that, with the scores obtained from the 40~60 authors in the database, the stability and the performance of the system become fairly comparable to the system with a maximum number of authors (720); and 2) that poor performance in terms of Cllr, which occurred because of limited background population data, is largely due to poor calibration. The results also indicated that the score-based approach is more robust against data scarcity than the feature-based approach; however, this finding obliges further study.
Anthology ID:
2020.alta-1.3
Volume:
Proceedings of the The 18th Annual Workshop of the Australasian Language Technology Association
Month:
December
Year:
2020
Address:
Virtual Workshop
Venue:
ALTA
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Publisher:
Australasian Language Technology Association
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Pages:
21–31
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URL:
https://aclanthology.org/2020.alta-1.3
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Cite (ACL):
Shunichi Ishihara. 2020. The Influence of Background Data Size on the Performance of a Score-based Likelihood Ratio System: A Case of Forensic Text Comparison. In Proceedings of the The 18th Annual Workshop of the Australasian Language Technology Association, pages 21–31, Virtual Workshop. Australasian Language Technology Association.
Cite (Informal):
The Influence of Background Data Size on the Performance of a Score-based Likelihood Ratio System: A Case of Forensic Text Comparison (Ishihara, ALTA 2020)
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https://aclanthology.org/2020.alta-1.3.pdf