A comparison of graph-based word sense induction clustering algorithms in a pseudoword evaluation framework
Sign Up to like & getrecommendations! Published in 2018 at "Language Resources and Evaluation"
DOI: 10.1007/s10579-018-9415-1
Abstract: Abstract This article presents a comparison of different Word Sense Induction (wsi) clustering algorithms on two novel pseudoword data sets of semantic-similarity and co-occurrence-based word graphs, with a special focus on the detection of homonymic… read more here.
Keywords: word; clustering algorithms; pseudoword; graph ... See more keywords
Outlier detection using an ensemble of clustering algorithms
Sign Up to like & getrecommendations! Published in 2022 at "Multimedia Tools and Applications"
DOI: 10.1007/s11042-021-11671-9
Abstract: Outlier detection is an important research area in the field of machine learning and data science. The presence of outliers in a dataset limits its true usefulness in a real-life scenario. Due to the varied… read more here.
Keywords: outlier detection; clustering algorithms; using ensemble; detection using ... See more keywords
An overview of recent multi-view clustering
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DOI: 10.1016/j.neucom.2020.02.104
Abstract: Abstract With the widespread deployment of sensors and the Internet-of-Things, multi-view data has become more common and publicly available. Compared to traditional data that describes objects from single perspective, multi-view data is semantically richer, more… read more here.
Keywords: view clustering; overview recent; view; clustering algorithms ... See more keywords
Fundamental clustering algorithms suite
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DOI: 10.1016/j.softx.2020.100642
Abstract: Abstract The article presents immediate access to over fifty fundamental clustering algorithms. Additionally, access to clustering benchmark datasets published priorly as “Fundamental Clustering Problems Suite” (FCPS) is provided. The software library is named “FCPS”, available… read more here.
Keywords: algorithms suite; fundamental clustering; cluster; clustering algorithms ... See more keywords
A comparative analysis of clustering algorithms to identify the homogeneous rainfall gauge stations of Bangladesh
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DOI: 10.1080/02664763.2019.1675606
Abstract: ABSTRACT Dealing with individual rainfall station is time consuming as well as prone to more variation. It seems reasonable and advantageous to deal with a group of homogeneous stations rather than an individual station. Such… read more here.
Keywords: comparative analysis; means clustering; clustering algorithms; rainfall ... See more keywords
Expediency Analysis of Clustering Algorithms for Electric Two-Wheeler Driving Cycle Development Under Indian Smart City Driving Conditions
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Access"
DOI: 10.1109/access.2024.3508754
Abstract: The standard driving cycles (DCs) used to evaluate spark-ignition engine-based two-wheelers are inadequate for electric two-wheelers (E2Ws). Also, they fail to accurately represent the actual driving circumstances in specific areas, resulting in inaccuracies during the… read more here.
Keywords: electric two; clustering algorithms; driving; two wheeler ... See more keywords
On Evaluation of Data Stream Clustering Algorithms: A Survey
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Access"
DOI: 10.1109/access.2025.3596435
Abstract: Data stream mining is a research area that has grown enormously in recent years. The main challenge is extracting knowledge in real-time from a possibly unbounded data stream. Clustering, a process in which groupings within… read more here.
Keywords: stream clustering; survey; clustering algorithms; data stream ... See more keywords
TDEC: Evidential Clustering Based on Transfer Learning and Deep Autoencoder
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Transactions on Fuzzy Systems"
DOI: 10.1109/tfuzz.2024.3421564
Abstract: Evidential clustering is a promising clustering framework using Dempster–Shafer belief function theory to model uncertain data. However, evidential clustering needs to estimate more parameters compared with other clustering algorithms, and thus the clustering performance of… read more here.
Keywords: deep autoencoder; evidential clustering; clustering algorithms; transfer ... See more keywords
Directed Graph Clustering Algorithms, Topology, and Weak Links
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Systems, Man, and Cybernetics: Systems"
DOI: 10.1109/tsmc.2021.3087591
Abstract: In this article, a general approach for directed graph clustering and two new density-based clustering objectives are presented. First, using an equivalence between the clustering objective functions and a trace maximization expression, the directed graph… read more here.
Keywords: topology; directed graph; weak links; clustering algorithms ... See more keywords
Comparison and Analysis of Several Clustering Algorithms for Pavement Crack Segmentation Guided by Computational Intelligence
Sign Up to like & getrecommendations! Published in 2022 at "Computational Intelligence and Neuroscience"
DOI: 10.1155/2022/8965842
Abstract: Cracks are one of the most common types of imperfections that can be found in concrete pavement, and they have a significant influence on the structural strength. The purpose of this study is to investigate… read more here.
Keywords: crack; pavement crack; clustering algorithms; comparison ... See more keywords
Application of Clustering Algorithms to TRMM Precipitation over the Tropical and South Pacific Ocean
Sign Up to like & getrecommendations! Published in 2020 at "Journal of Climate"
DOI: 10.1175/jcli-d-19-0537.1
Abstract: AbstractUnderstanding multiscale rainfall variability in the South Pacific convergence zone (SPCZ), a southeastward-oriented band of precipitating deep convection in the South Pacific, is critical ... read more here.
Keywords: south pacific; clustering algorithms; algorithms trmm; application clustering ... See more keywords