An incremental CFS algorithm for clustering large data in industrial internet of things
With the rapid advances of sensing technologies and wireless communications, large
amounts of dynamic data pertaining to industrial production are being collected from many …
amounts of dynamic data pertaining to industrial production are being collected from many …
ICFS clustering with multiple representatives for large data
With the prevailing development of Cyber-physical-social systems and Internet of Things,
large-scale data have been collected consistently. Mining large data effectively and …
large-scale data have been collected consistently. Mining large data effectively and …
A grid-based clustering algorithm via load analysis for industrial internet of things
J Zhang, X Feng, Z Liu - IEEE Access, 2018 - ieeexplore.ieee.org
In the Industrial Internet of Things (IIoT), wireless sensor network (WSN) technology makes
devices that communicate with each other. The information integrated from multiple data …
devices that communicate with each other. The information integrated from multiple data …
Scalable clustering algorithms for big data: A review
Clustering algorithms have become one of the most critical research areas in multiple
domains, especially data mining. However, with the massive growth of big data applications …
domains, especially data mining. However, with the massive growth of big data applications …
Fuzzy based scalable clustering algorithms for handling big data using apache spark
A huge amount of digital data containing useful information, called Big Data, is generated
everyday. To mine such useful information, clustering is widely used data analysis …
everyday. To mine such useful information, clustering is widely used data analysis …
An incremental density-based clustering framework using fuzzy local clustering
S Laohakiat, V Sa-Ing - Information Sciences, 2021 - Elsevier
This paper presents a novel incremental density-based clustering framework using the one-
pass scheme, named Fuzzy Incremental Density-based Clustering (FIDC). Employing one …
pass scheme, named Fuzzy Incremental Density-based Clustering (FIDC). Employing one …
DENCLUE-IM: A new approach for big data clustering
H Rehioui, A Idrissi, M Abourezq, F Zegrari - Procedia Computer Science, 2016 - Elsevier
Every day, a large volume of data is generated by multiple sources, social networks, mobile
devices, etc. This variety of data sources produce an heterogeneous data, which are …
devices, etc. This variety of data sources produce an heterogeneous data, which are …
Dense members of local cores-based density peaks clustering algorithm
D Cheng, S Zhang, J Huang - Knowledge-Based Systems, 2020 - Elsevier
An efficient clustering algorithm by fast search and find of density peaks (DP) was proposed
and attracted much attention from researchers. It assumes that cluster centers are …
and attracted much attention from researchers. It assumes that cluster centers are …
Clustering of big data in cloud environments for smart applications
New worries and difficulties in data management and analysis have arisen in response to
the fast rise of big data in the IT sector. Common difficulties include those of scale, velocity …
the fast rise of big data in the IT sector. Common difficulties include those of scale, velocity …
Data mining at the IoT edge
C Savaglio, P Gerace, G Di Fatta… - 2019 28th international …, 2019 - ieeexplore.ieee.org
The Internet of Things (IoT) enables the interconnection of new cyber-physical devices
which generate significant traffic of distributed, heterogeneous and dynamic data at the …
which generate significant traffic of distributed, heterogeneous and dynamic data at the …