A Short Review on Different Clustering Techniques and Their Applications

Ghosal, Attri; Nandy, Arunima; Das, Amit Kumar; Goswami, Saptarsi; Panday, Mrityunjoy

doi:10.1007/978-981-13-7403-6_9

Cited by 83 publications

(48 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Consequently, data within the same cluster will be more similar compared to those in other clusters. In the literature, clustering approach is broadly adapted to many sectors including, but not limited to, security, business, transportation, and healthcare applications [26] [27] [28]. Researchers have proposed several data clustering algorithms such as mean-shift, density-based spatial clustering of applications with noise, expectation-maximization using Gaussian mixture models, agglomerative hierarchical, etc.…”

Section: Data Clustering Stagementioning

confidence: 99%

CRISE: Toward Better Understanding of COVID-19 Psychological Impact during Lockdown

Baalbaki¹,

Harb²,

Zaki³

et al. 2021

JCC

View full text Add to dashboard Cite

Recently, the COVID-19 emerged in China and propagated around all the world has threatened millions of people and affected most countries and governments at several sides such as economical, educational, tourism, healthcare, etc. Indeed, one of the most important challenges that directly affect the people is the psychological side due to the harsh policies imposed by public authorities in most countries. In this paper, we propose a framework called CRISE that allows studying and understanding the psychological effect of COVID-19 during the lockdown period. Mainly, CRISE consists of four data stages: Collection, tRansformation, reductIon, and cluStEring. The first stage collects data from more than 2000 participants through a questionnaire containing attributes related to psychological effect before and during the lockdown. The second stage aims to preprocess the data before performing the study stage. The third stage proposes a model that finds the similarities among the attributes, based on the correlation matrix, to reduce its number. Finally, the fourth stage introduces a new version of Kmeans algorithm, called as Jaccard-based Kmeans (JKmeans), that allows to group participants having similar psychological situation in the same cluster for a later analysis. We show the effectiveness of CRISE in terms of clustering accuracy and understanding the psychological effect of COVID-19.

show abstract

Section: Data Clustering Stagementioning

confidence: 99%

CRISE: Toward Better Understanding of COVID-19 Psychological Impact during Lockdown

Baalbaki¹,

Harb²,

Zaki³

et al. 2021

JCC

View full text Add to dashboard Cite

show abstract

“…Hierarchical clustering is well-known in data science and its outperformance is verified in several applications [19]. This approach involves creating a hierarchy of clusters [25].…”

Section: Hierarchical Spectral Clustering Theorymentioning

confidence: 99%

“…• Improving the hierarchical clustering algorithm: Hierarchical clustering is known as an effective method in data science [19], which is easy to implement. However, it is not possible to include the restriction on the aggregation of vertices in the optimization process.…”

Section: Introductionmentioning

confidence: 99%

An Effective Multi-Solution Approach for Power System Islanding

et al. 2020

View full text Add to dashboard Cite

“…A general statistical analysis regarding different data clustering algorithms based on research paper up to date has been provided in the [2]. Top 5 most usable and implemented into various applications data clustering algorithms have been described previously in [11]. It claims that no single clustering algorithm has been found to dominate all areas of implementation and thus there is still vast scope of research and development in data mining [11].…”

Section: Related Workmentioning

confidence: 99%

A Conceptual review on different data clustering algorithms and a proposed insight into their applicability in the context of Covid-19

2020

J. adv. tec. eng. res.

View full text Add to dashboard Cite

show abstract

A Short Review on Different Clustering Techniques and Their Applications

Cited by 83 publications

References 28 publications

CRISE: Toward Better Understanding of COVID-19 Psychological Impact during Lockdown

CRISE: Toward Better Understanding of COVID-19 Psychological Impact during Lockdown

An Effective Multi-Solution Approach for Power System Islanding

A Conceptual review on different data clustering algorithms and a proposed insight into their applicability in the context of Covid-19

Contact Info

Product

Resources

About