Temporal language models for the disclosure of historical text
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The document discusses temporal language models for classifying historical texts by date without metadata timestamps. It outlines analyzing normalized log-likelihood ratios across time-partitioned reference corpora to determine the most likely partition and therefore date range of an unknown document. The approach assumes related word usage evolves predictably over time and aims to enhance search by suggesting diachronically similar synonyms to users.
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Temporal language models for the disclosure of historical text
- 1. Temporal language models for the disclosure of historical text Franciska de Jong, Henning Rode, and Djoerd Hiemstra 2005
- 5. 5
- 6. 3 6 generated by Dave Farrance, using Google's n-gram viewer
- 7. Normalized log-likelihood ratio ( NLLR ) 7
- 8. 8
- 9. where t i marks a partition within the corpus period ( t 0 would indicate the beginning of the corpus period); C i denotes a partition of corpus documents; D j denotes any document from the corpus; and τ(D j ) indicates the document's presumed date. Time partitioning 9
- 10. 10
- 12. Two methods 12