Efficient natural language classification algorithm for detecting duplicate unsupervised features

This paper focuses on capturing the meaning of Natural Language Understanding (NLU) text features to detect the duplicate unsupervised features. The NLU features are compared with lexical approaches to prove the suitable classification technique. The transfer-learning approach is utilized to train t...

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Autori principali:	Saud Altaf, Sofia Iqbal, Muhammad Waseem Soomro
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	Russian Academy of Sciences, St. Petersburg Federal Research Center 2021-06-01
Serie:	Информатика и автоматизация
Soggetti:	clustering information retrieval large data sets natural language texts lexical ap-proaches classification training.
Accesso online:	http://ia.spcras.ru/index.php/sp/article/view/13265
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