Abstract
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.
Cite
CITATION STYLE
Niculae, V., Zampieri, M., Dinu, L. P., & Ciobanu, A. M. (2014). Temporal Text Ranking and Automatic Dating of Texts. In EACL 2014 - 14th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings of the Conference (pp. 17–21). Association for Computational Linguistics (ACL). https://doi.org/10.3115/v1/e14-4004
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