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Information-Theoretic method for classification of texts. / Ryabko, B. Ya; Gus’kov, A. E.; Selivanova, I. V.

In: Problems of Information Transmission, Vol. 53, No. 3, 01.07.2017, p. 294-304.

Research output: Contribution to journal › Article › peer-review

Harvard

Ryabko, BY, Gus’kov, AE & Selivanova, IV 2017, 'Information-Theoretic method for classification of texts', Problems of Information Transmission, vol. 53, no. 3, pp. 294-304. https://doi.org/10.1134/S0032946017030115

APA

Ryabko, B. Y., Gus’kov, A. E., & Selivanova, I. V. (2017). Information-Theoretic method for classification of texts. Problems of Information Transmission, 53(3), 294-304. https://doi.org/10.1134/S0032946017030115

Vancouver

Ryabko BY, Gus’kov AE, Selivanova IV. Information-Theoretic method for classification of texts. Problems of Information Transmission. 2017 Jul 1;53(3):294-304. doi: 10.1134/S0032946017030115

Author

Ryabko, B. Ya ; Gus’kov, A. E. ; Selivanova, I. V. / Information-Theoretic method for classification of texts. In: Problems of Information Transmission. 2017 ; Vol. 53, No. 3. pp. 294-304.

BibTeX

@article{a7c0520104494552a51ee4acf6e06f80,
title = "Information-Theoretic method for classification of texts",
abstract = "We consider a method for automatic (i.e., unmanned) text classification based on methods of universal source coding (or “data compression”). We show that under certain restrictions the proposed method is consistent, i.e., the classification error tends to zero with increasing text lengths. As an example of practical use of the method we consider the classification problem for scientific texts (research papers, books, etc.). The proposed method is experimentally shown to be highly efficient.",
author = "Ryabko, {B. Ya} and Gus{\textquoteright}kov, {A. E.} and Selivanova, {I. V.}",
year = "2017",
month = jul,
day = "1",
doi = "10.1134/S0032946017030115",
language = "English",
volume = "53",
pages = "294--304",
journal = "Problems of Information Transmission",
issn = "0032-9460",
publisher = "Maik Nauka-Interperiodica Publishing",
number = "3",

}

RIS

TY - JOUR

T1 - Information-Theoretic method for classification of texts

AU - Ryabko, B. Ya

AU - Gus’kov, A. E.

AU - Selivanova, I. V.

PY - 2017/7/1

Y1 - 2017/7/1

N2 - We consider a method for automatic (i.e., unmanned) text classification based on methods of universal source coding (or “data compression”). We show that under certain restrictions the proposed method is consistent, i.e., the classification error tends to zero with increasing text lengths. As an example of practical use of the method we consider the classification problem for scientific texts (research papers, books, etc.). The proposed method is experimentally shown to be highly efficient.

AB - We consider a method for automatic (i.e., unmanned) text classification based on methods of universal source coding (or “data compression”). We show that under certain restrictions the proposed method is consistent, i.e., the classification error tends to zero with increasing text lengths. As an example of practical use of the method we consider the classification problem for scientific texts (research papers, books, etc.). The proposed method is experimentally shown to be highly efficient.

UR - http://www.scopus.com/inward/record.url?scp=85031754667&partnerID=8YFLogxK

U2 - 10.1134/S0032946017030115

DO - 10.1134/S0032946017030115

M3 - Article

AN - SCOPUS:85031754667

VL - 53

SP - 294

EP - 304

JO - Problems of Information Transmission

JF - Problems of Information Transmission

SN - 0032-9460

IS - 3

ER -

ID: 9410463