Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Lena Zhetkenbay"'
Autor:
Nurzada Amangeldy, Marek Milosz, Saule Kudubayeva, Akmaral Kassymova, Gulsim Kalakova, Lena Zhetkenbay
Publikováno v:
Applied Sciences, Vol 13, Iss 19, p 10799 (2023)
Among the many problems in machine learning, the most critical ones involve improving the categorical response prediction rate based on extracted features. In spite of this, it is noted that most of the time from the entire cycle of multi-class machi
Externí odkaz:
https://doaj.org/article/3c0133cb0e464bf4aaa7ba94979771f8
Publikováno v:
Вестник Алматинского университета энергетики и связи. :230-236
Publikováno v:
Computational Science and Its Applications – ICCSA 2020 ISBN: 9783030588014
ICCSA (2)
ICCSA (2)
This paper describes characteristics which affect the sentiment analysis in the Kazakh language texts, models of morphological rules and morphological analysis algorithms, formal models of simple sentence structures in the Kazakh-Turkish combination,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fb2f974f12db3750355cf8d899ecf553
https://doi.org/10.1007/978-3-030-58802-1_38
https://doi.org/10.1007/978-3-030-58802-1_38
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783319476735
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9f505bf495c4fe3b0c40ebf93a327bf5
https://doi.org/10.1007/978-3-319-47674-2_38
https://doi.org/10.1007/978-3-319-47674-2_38
Investigation and Use of Methods for Defining the Extends of Similarity of Kazakh Language Sentences
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783319476735
CCL
CCL
Finding similarity degree is one of the significant technologies used in the sample-based machine translation. It works in the following principle, first matching the input sentences with a sentence in the sample database, after that it is necessary
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::62bd300caf112577e3841f851772a180
https://doi.org/10.1007/978-3-319-47674-2_14
https://doi.org/10.1007/978-3-319-47674-2_14