Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
Paperpass检测
checkpass检测
PaperYY检测
Semi-supervised constrained clustering: An in-depth overview, ranked taxonomy and future research directions
G González-Almagro, D Peralta, E De Poorter… - ar** discrete sets of instances with similar characteristics. Constrained …
Semi-supervised clustering under a “compact-cluster” assumption
Semi-supervised clustering (SSC) aims to improve clustering performance with the support
of prior knowledge (ie, side information). Compared with pairwise constraints, the partial …
of prior knowledge (ie, side information). Compared with pairwise constraints, the partial …
A classification-based approach to semi-supervised clustering with pairwise constraints
In this paper, we introduce a neural network framework for semi-supervised clustering with
pairwise (must-link or cannot-link) constraints. In contrast to existing approaches, we …
pairwise (must-link or cannot-link) constraints. In contrast to existing approaches, we …
An effective clustering scheme for high-dimensional data
X He, F He, Y Fan, L Jiang, R Liu, A Maalla - Multimedia Tools and …, 2024 - Springer
While the classical K-means algorithm has been widely used in many fields, it still has some
defects. Therefore, this paper proposes a scheme to improve the clustering quality of K …
defects. Therefore, this paper proposes a scheme to improve the clustering quality of K …
Cross-entropy clustering framework for catchment classification
There is an increasing interest in catchment classification and regionalization in hydrology,
as they are useful for identification of appropriate model complexity and transfer of …
as they are useful for identification of appropriate model complexity and transfer of …
COBRASTS: A New Approach to Semi-supervised Clustering of Time Series
Clustering is ubiquitous in data analysis, including analysis of time series. It is inherently
subjective: different users may prefer different clusterings for a particular dataset. Semi …
subjective: different users may prefer different clusterings for a particular dataset. Semi …
[Retracted] Construction of Data Resource Sharing Platform for College Students' Ideological and Political Education Based on Constraint Clustering
J Cheng - Wireless Communications and Mobile Computing, 2022 - Wiley Online Library
Online learning communities have changed the “silo” learning structure of traditional online
learning and provided an effective support environment for wisdom sharing and …
learning and provided an effective support environment for wisdom sharing and …
[HTML][HTML] Active function cross-entropy clustering
Abstract Gaussian Mixture Models (GMM) have many applications in density estimation and
data clustering. However, the models do not adapt well to curved and strongly nonlinear …
data clustering. However, the models do not adapt well to curved and strongly nonlinear …
General split gaussian cross–entropy clustering
Robust mixture models approaches, which use non-normal distributions have recently been
upgraded to accommodate asymmetric data. In this article we propose a new method based …
upgraded to accommodate asymmetric data. In this article we propose a new method based …
Kernel-estimated nonparametric overlap-based syncytial clustering
Commonly-used clustering algorithms usually find ellipsoidal, spherical or other regular-
structured clusters, but are more challenged when the underlying groups lack formal …
structured clusters, but are more challenged when the underlying groups lack formal …