2025-02-22T01:24:40-05:00 DEBUG: VuFindSearch\Backend\Solr\Connector: Query fl=%2A&wt=json&json.nl=arrarr&q=id%3A%22drspiprikievua-article-178945%22&qt=morelikethis&rows=5
2025-02-22T01:24:40-05:00 DEBUG: VuFindSearch\Backend\Solr\Connector: => GET http://localhost:8983/solr/biblio/select?fl=%2A&wt=json&json.nl=arrarr&q=id%3A%22drspiprikievua-article-178945%22&qt=morelikethis&rows=5
2025-02-22T01:24:40-05:00 DEBUG: VuFindSearch\Backend\Solr\Connector: <= 200 OK
2025-02-22T01:24:40-05:00 DEBUG: Deserialized SOLR response
Method of the coherence evaluation of Ukrainian text.

Method of the coherence evaluation of Ukrainian text.

Due to the growing role of the SEO technologies, it is necessary to perform an automated analysis of the article’s quality. Such an approach helps both to return the most intelligible pages for the user’s query and to raise the web-sites positions to the top of query results. An automated assessment...

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Bibliographic Details
Main Authors: Pogorilyy, S. D., Kramov, A. A.
Format: Article
Language:Ukrainian
Published: Інститут проблем реєстрації інформації НАН України 2019
Subjects:
обробка природної мови
когерентність тексту
граф семантичної схожості
нейронна мережа
модель Doc2Vec
семантична міра схожості речень
natural language processing
text coherence
semantic similarity graph
neural network
Doc2Vec model
semantic similarity value of sentences
Online Access:http://drsp.ipri.kiev.ua/article/view/178945
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