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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 …
learning and clustering analysis, incorporates the given prior information (eg, class labels …
A new approach for semi-supervised fuzzy clustering with multiple fuzzifiers
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 …
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
Categorizing residential energy demand patterns is a principal task for demand-side
management (DSM) and energy-saving strategies. While deep learning (DL)-based …
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 …
classify text according to topic and sentiment, which has drawn much interest in recent …
Robust semi-supervised clustering via data transductive war**
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 …
amount of independent class label or constraint information and many unlabeled instances …
End-to-end novel visual categories learning via auxiliary self-supervision
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 …
annotations in deep learning. However, most of the methods have adopted a common …