A similarity-based semi-supervised algorithm for labeling unlabeled text data

This paper presents a novel, non-iterative semi-supervised learning algorithm that leverages cosine similarity between document vectors and class mean vectors to label unlabeled text data automatically. The proposed method supports multiple vectorization techniques, including CountVectorizer, TF-IDF...

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Bibliographic Details

Published in:	Expert systems with applications Vol. 296; p. 128941
Main Authors:	Potshangbam, Kirankumar Singh, Singh, Kshetrimayum Nareshkumar
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 15.01.2026
Subjects:	Semi-supervised learning Similarity measure Text classification Vector representation Similarity measure Semi-supervised learning Vector representation Text classification
ISSN:	0957-4174
Online Access:	Get full text
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