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- W2903068667 abstract "Text language recognition is necessary for formal analysis of texts. The paper describes the algorithm based on frequency characteristics to identify Russian language texts varied in size. Required to solve the problem, unigram and big ram characteristics (the number of characters, big rams and digrams being used, frequency of each character) and based on them criteria (the coincidence index, the conj unction index, and comprehensiveness of characters and bigrams being used in the text) are determined. Critical values and application ways for the criteria are determined. The algorithm accuracy is obtained experimentally for different samples. Compared to machine learning methods (such as neural networks or naive Bayes classifiers), the algorithm does not require additional information and training samples, simple in implementation and rather efficient in computing." @default.
- W2903068667 created "2018-12-11" @default.
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- W2903068667 date "2018-10-01" @default.
- W2903068667 modified "2023-09-26" @default.
- W2903068667 title "Criteria and Algorithm for the Russian Language Text Recognition Based on the Frequency Characteristics Set" @default.
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- W2903068667 doi "https://doi.org/10.1109/apeie.2018.8545877" @default.
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