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...

Celý popis

Podrobná bibliografia

Vydané v:	Expert systems with applications Ročník 296; s. 128941
Hlavní autori:	Potshangbam, Kirankumar Singh, Singh, Kshetrimayum Nareshkumar
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier Ltd 15.01.2026
Predmet:	Semi-supervised learning Similarity measure Text classification Vector representation Similarity measure Semi-supervised learning Vector representation Text classification
ISSN:	0957-4174
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!