A review on semi-supervised clustering

J Cai, J Hao, H Yang, X Zhao, Y Yang - Information Sciences, 2023‏ - Elsevier
Abstract Semi-supervised clustering (SSC), a technique integrating semi-supervised
learning and clustering analysis, incorporates the given prior information (eg, class labels …

A new approach for semi-supervised fuzzy clustering with multiple fuzzifiers

TM Tuan, MD Sinh, TĐ Khang, PT Huan… - International Journal of …, 2022‏ - Springer
Data clustering is the process of dividing data elements into different clusters in which
elements in one cluster have more similarity than those in other clusters. Semi-supervised …

Time-series data clustering with load-shape preservation for identifying residential energy consumption behaviors

J Kim, K Song, G Lee, SH Lee - Energy and Buildings, 2024‏ - Elsevier
Categorizing residential energy demand patterns is a principal task for demand-side
management (DSM) and energy-saving strategies. While deep learning (DL)-based …

[PDF][PDF] An improved deep text clustering via local manifold of an autoencoder embedding

K Berahmand, F Daneshfar, M Dorosti, MJ Aghajani - 2022‏ - academia.edu
Text clustering is a method for separating speci c information from textual data and can even
classify text according to topic and sentiment, which has drawn much interest in recent …

Robust semi-supervised clustering via data transductive war**

P Zhou, N Wang, S Zhao, Y Zhang - Applied Intelligence, 2023‏ - Springer
In practical applications, we are more likely to face semi-supervised data with a small
amount of independent class label or constraint information and many unlabeled instances …

End-to-end novel visual categories learning via auxiliary self-supervision

Y Qing, Y Zeng, Q Cao, GB Huang - Neural Networks, 2021‏ - Elsevier
Semi-supervised learning has largely alleviated the strong demand for large amount of
annotations in deep learning. However, most of the methods have adopted a common …