Clustering Large Datasets Using Data Stream Clustering Techniques

2013 ◽  
pp. 135-143 ◽  
Author(s):  
Matthew Bolaños ◽  
John Forrest ◽  
Michael Hahsler
Keyword(s):  
Data Stream ◽  
Large Datasets ◽  
Clustering Techniques ◽  
Stream Clustering ◽  
Data Stream Clustering ◽  
Using Data

Twitter spammer detection using data stream clustering

2014 ◽  
Vol 260 ◽  
pp. 64-73 ◽  
Author(s):  
Zachary Miller ◽  
Brian Dickinson ◽  
William Deitrick ◽  
Wei Hu ◽  
Alex Hai Wang
Keyword(s):  
Data Stream ◽  
Stream Clustering ◽  
Data Stream Clustering ◽  
Using Data

IMPROVED DENSITY BASED ALGORITHM FOR DATA STREAM CLUSTERING

2015 ◽  
Vol 77 (18) ◽  
Author(s):  
Maryam Mousavi ◽  
Azuraliza Abu Bakar
Keyword(s):  
Data Streams ◽  
Data Stream ◽  
Clustering Algorithm ◽  
Local Density ◽  
Clustering Methods ◽  
Clustering Techniques ◽  
Stream Clustering ◽  
Density Based Clustering ◽  
Clustering Quality ◽  
Data Stream Clustering

In recent years, clustering methods have attracted more attention in analysing and monitoring data streams. Density-based techniques are the remarkable category of clustering techniques that are able to detect the clusters with arbitrary shapes and noises. However, finding the clusters with local density varieties is a difficult task. For handling this problem, in this paper, a new density-based clustering algorithm for data streams is proposed. This algorithm can improve the offline phase of density-based algorithm based on MinPts parameter. The experimental results show that the proposed technique can improve the clustering quality in data streams with different densities.

Survey on Data Streams Clustering Techniques

2014 ◽  
Vol 933 ◽  
pp. 768-773 ◽  
Author(s):  
Wei Hua Ma
Keyword(s):  
Big Data ◽  
Data Streams ◽  
Data Stream ◽  
Research Topic ◽  
Sliding Windows ◽  
Clustering Techniques ◽  
Research Results ◽  
Stream Clustering ◽  
Data Stream Clustering

Data stream in a popular research topic in big data era. There are many research results on data stream clustering domain. This paper firstly has a brief introduction to data stream methodologies, such as sampling, sliding windows, etc. Finally, it presents a survey on data streams clustering techniques.

Data stream clustering based on Fuzzy C-Mean algorithm and entropy theory

2016 ◽  
Vol 126 ◽  
pp. 111-116 ◽  
Author(s):  
Baoju Zhang ◽  
Shan Qin ◽  
Wei Wang ◽  
Dan Wang ◽  
Lei Xue
Keyword(s):  
Data Stream ◽  
Entropy Theory ◽  
Stream Clustering ◽  
Data Stream Clustering

Evolving Data Monitoring Algorithm based on Data Stream Clustering

2021 ◽  
Vol 1955 (1) ◽  
pp. 012048
Author(s):  
Chunhua Yang ◽  
Cong Wang ◽  
Xiao Hu ◽  
Niankang You ◽  
Xuguang Yang
Keyword(s):  
Data Stream ◽  
Data Monitoring ◽  
Stream Clustering ◽  
Data Stream Clustering ◽  
Evolving Data ◽  
Monitoring Algorithm
Sign in / Sign up

Export Citation Format

Share Document