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Dataset of stopwords extracted from Uzbek texts
Filtering stop words is an important task when processing text queries to search for information in large data sets. It enables a reduction of the search space without losing the semantic meaning. The stop words, which have only grammatical roles and not contributing to information content still add...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9194838/ https://www.ncbi.nlm.nih.gov/pubmed/35712366 http://dx.doi.org/10.1016/j.dib.2022.108351 |
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author | Madatov, Khabibulla Bekchanov, Shukurla Vičič, Jernej |
author_facet | Madatov, Khabibulla Bekchanov, Shukurla Vičič, Jernej |
author_sort | Madatov, Khabibulla |
collection | PubMed |
description | Filtering stop words is an important task when processing text queries to search for information in large data sets. It enables a reduction of the search space without losing the semantic meaning. The stop words, which have only grammatical roles and not contributing to information content still add up to the complexity of the query. Existing mathematical models that are used to tackle this problem are not suitable for all families of natural languages [1]. For example, they do not cover families of languages to which Uzbek can be included. In the present work, the collocation method of this problem is o ered for families of languages that include the Uzbek language as well. This method concerns the so-called agglutinative languages, in which the task of recognizing stop words is much more difficult, since the stop words are “masked” in the text. In this work the unigram, the bigram and the collocation methods are applied to the “School corpus” that corresponds to the type of languages being studied. |
format | Online Article Text |
id | pubmed-9194838 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-91948382022-06-15 Dataset of stopwords extracted from Uzbek texts Madatov, Khabibulla Bekchanov, Shukurla Vičič, Jernej Data Brief Data Article Filtering stop words is an important task when processing text queries to search for information in large data sets. It enables a reduction of the search space without losing the semantic meaning. The stop words, which have only grammatical roles and not contributing to information content still add up to the complexity of the query. Existing mathematical models that are used to tackle this problem are not suitable for all families of natural languages [1]. For example, they do not cover families of languages to which Uzbek can be included. In the present work, the collocation method of this problem is o ered for families of languages that include the Uzbek language as well. This method concerns the so-called agglutinative languages, in which the task of recognizing stop words is much more difficult, since the stop words are “masked” in the text. In this work the unigram, the bigram and the collocation methods are applied to the “School corpus” that corresponds to the type of languages being studied. Elsevier 2022-06-03 /pmc/articles/PMC9194838/ /pubmed/35712366 http://dx.doi.org/10.1016/j.dib.2022.108351 Text en © 2022 The Authors. Published by Elsevier Inc. https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Data Article Madatov, Khabibulla Bekchanov, Shukurla Vičič, Jernej Dataset of stopwords extracted from Uzbek texts |
title | Dataset of stopwords extracted from Uzbek texts |
title_full | Dataset of stopwords extracted from Uzbek texts |
title_fullStr | Dataset of stopwords extracted from Uzbek texts |
title_full_unstemmed | Dataset of stopwords extracted from Uzbek texts |
title_short | Dataset of stopwords extracted from Uzbek texts |
title_sort | dataset of stopwords extracted from uzbek texts |
topic | Data Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9194838/ https://www.ncbi.nlm.nih.gov/pubmed/35712366 http://dx.doi.org/10.1016/j.dib.2022.108351 |
work_keys_str_mv | AT madatovkhabibulla datasetofstopwordsextractedfromuzbektexts AT bekchanovshukurla datasetofstopwordsextractedfromuzbektexts AT vicicjernej datasetofstopwordsextractedfromuzbektexts |