Text Segmentation Via Processes that Count the Number of Different Words Forward and Backward Full article
| Journal |
Journal of Quantitative Linguistics
ISSN: 1744-5035 |
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| Output data | Year: 2024, Volume: 31, Number: 1, Pages: 1-18 Pages count : 18 DOI: 10.1080/09296174.2023.2275342 | ||||||||||
| Tags | change-point detection | ||||||||||
| Authors |
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| Affiliations |
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Funding (1)
| 1 | Sobolev Institute of Mathematics | FWNF-2022-0010 |
Abstract:
The paper is developing a new statistical approach to automatic partitioning of texts into parts belonging to different authors. It is based on the analysis of processes that counts the number of different words forward and backward. The theoretical study of the processes is based on the assumptions of an elementary probability model with a change point. We prove consistence of our statistical estimate of the point of concatenation in the case when the concatenated texts have different Zipf exponents. This method is being tested on the Brown corpus and also on newspaper texts in different languages. Testing shows a good estimate of the concatenation point. This method can be used in parallel with other text segmentation methods.
Cite:
Abebe B.
, Chebunin M.
, Kovalevskii A.
Text Segmentation Via Processes that Count the Number of Different Words Forward and Backward
Journal of Quantitative Linguistics. 2024. V.31. N1. P.1-18. DOI: 10.1080/09296174.2023.2275342 WOS Scopus OpenAlex
Text Segmentation Via Processes that Count the Number of Different Words Forward and Backward
Journal of Quantitative Linguistics. 2024. V.31. N1. P.1-18. DOI: 10.1080/09296174.2023.2275342 WOS Scopus OpenAlex
Dates:
| Published online: | Nov 12, 2023 |
| Published print: | Jan 15, 2024 |
Identifiers:
| Web of science: | WOS:001100158000001 |
| Scopus: | 2-s2.0-85176726465 |
| OpenAlex: | W4388608298 |