StreamLeader: A New Stream Clustering Algorithm not Based in Conventional Clustering

2016 ◽  
pp. 208-215
Author(s):  
Jaime Andrés-Merino ◽  
Lluís A. Belanche
Keyword(s):  
Clustering Algorithm ◽  
Stream Clustering

DGStream: High quality and efficiency stream clustering algorithm

2020 ◽  
Vol 141 ◽  
pp. 112947
Author(s):  
Rowanda Ahmed ◽  
Gökhan Dalkılıç ◽  
Yusuf Erten
Keyword(s):  
Clustering Algorithm ◽  
High Quality ◽  
Stream Clustering

Inline high-bandwidth network analysis using a robust stream clustering algorithm

2019 ◽  
Vol 13 (5) ◽  
pp. 486-495 ◽  
Author(s):  
Morteza Noferesti ◽  
Rasool Jalili
Keyword(s):  
Network Analysis ◽  
Clustering Algorithm ◽  
Stream Clustering ◽  
High Bandwidth

Text stream clustering algorithm based on adaptive feature selection

2011 ◽  
Vol 38 (3) ◽  
pp. 1393-1399 ◽  
Author(s):  
Linghui Gong ◽  
Jianping Zeng ◽  
Shiyong Zhang
Keyword(s):  
Feature Selection ◽  
Clustering Algorithm ◽  
Stream Clustering ◽  
Adaptive Feature Selection

scholarly journals EvolveCluster: an evolutionary clustering algorithm for streaming data

2021 ◽  
Author(s):  
Christian Nordahl ◽  
Veselka Boeva ◽  
Håkan Grahn ◽  
Marie Persson Netz
Keyword(s):  
Data Streams ◽  
Data Stream ◽  
Clustering Algorithm ◽  
Clustering Algorithms ◽  
Streaming Data ◽  
Evolutionary Clustering ◽  
Stream Clustering ◽  
The Past ◽  
Data Stream Clustering ◽  
Evolving Data

AbstractData has become an integral part of our society in the past years, arriving faster and in larger quantities than before. Traditional clustering algorithms rely on the availability of entire datasets to model them correctly and efficiently. Such requirements are not possible in the data stream clustering scenario, where data arrives and needs to be analyzed continuously. This paper proposes a novel evolutionary clustering algorithm, entitled EvolveCluster, capable of modeling evolving data streams. We compare EvolveCluster against two other evolutionary clustering algorithms, PivotBiCluster and Split-Merge Evolutionary Clustering, by conducting experiments on three different datasets. Furthermore, we perform additional experiments on EvolveCluster to further evaluate its capabilities on clustering evolving data streams. Our results show that EvolveCluster manages to capture evolving data stream behaviors and adapts accordingly.

A Markov Chain Load Modeling Approach through a Stream Clustering Algorithm

2020 ◽  
Author(s):  
Stefano Massucco ◽  
Gabriele Mosaico ◽  
Matteo Saviozzi ◽  
Federico Silvestro ◽  
Antonio Fidigatti ◽  
...  
Keyword(s):  
Markov Chain ◽  
Clustering Algorithm ◽  
Load Modeling ◽  
Stream Clustering ◽  
Modeling Approach

Distributed data stream clustering algorithm based on affinity propagation

2013 ◽  
Vol 33 (9) ◽  
pp. 2477-2481
Author(s):  
Jianpeng ZHANG ◽  
Xin JIN ◽  
Fucai CHEN ◽  
Hongchang CHEN ◽  
Ying HOU
Keyword(s):  
Data Stream ◽  
Clustering Algorithm ◽  
Affinity Propagation ◽  
Distributed Data ◽  
Stream Clustering ◽  
Data Stream Clustering
Sign in / Sign up

Export Citation Format

Share Document