Efficient natural language classification algorithm for detecting duplicate unsupervised features

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...

Full description

Bibliographic Details
Main Authors: Saud Altaf, Sofia Iqbal, Muhammad Waseem Soomro
Format: Article
Language:English
Published: Russian Academy of Sciences, St. Petersburg Federal Research Center 2021-06-01
Series:Информатика и автоматизация
Subjects:
clustering
information retrieval
large data sets
natural language texts
lexical ap-proaches
classification
training.
Online Access:http://ia.spcras.ru/index.php/sp/article/view/13265

Internet

http://ia.spcras.ru/index.php/sp/article/view/13265

Similar Items