Temporal Text Ranking and Automatic Dating of Texts

This paper presents a novel approach to the task of temporal text classification combining text ranking and probability for the automatic dating of historical texts. The method was applied to three historical corpora: an English, a Portuguese and a Romanian corpus. It obtained performance ranging from 83% to 93% accuracy, using a fully automated approach with very basic features.

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