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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…
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Keywords:
word;
clustering algorithms;
pseudoword;
graph ... See more keywords
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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…
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Keywords:
outlier detection;
clustering algorithms;
using ensemble;
detection using ... See more keywords
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Published in 2020 at "Neurocomputing"
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…
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Keywords:
view clustering;
overview recent;
view;
clustering algorithms ... See more keywords
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Published in 2021 at "SoftwareX"
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…
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Keywords:
algorithms suite;
fundamental clustering;
cluster;
clustering algorithms ... See more keywords
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Published in 2019 at "Journal of Applied Statistics"
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…
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Keywords:
comparative analysis;
means clustering;
clustering algorithms;
rainfall ... See more keywords
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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…
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Keywords:
topology;
directed graph;
weak links;
clustering algorithms ... See more keywords
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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…
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Keywords:
crack;
pavement crack;
clustering algorithms;
comparison ... See more keywords
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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 ...
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Keywords:
south pacific;
clustering algorithms;
algorithms trmm;
application clustering ... See more keywords
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Published in 2019 at "BMC Bioinformatics"
DOI: 10.1186/s12859-019-3089-6
Abstract: Cluster analysis is a core task in modern data-centric computation. Algorithmic choice is driven by factors such as data size and heterogeneity, the similarity measures employed, and the type of clusters sought. Familiarity and mere…
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Keywords:
robustness metric;
metric biological;
clustering algorithms;
data clustering ... See more keywords
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Published in 2022 at "Genome Biology"
DOI: 10.1186/s13059-022-02622-0
Abstract: Background A key task in single-cell RNA-seq (scRNA-seq) data analysis is to accurately detect the number of cell types in the sample, which can be critical for downstream analyses such as cell type identification. Various…
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Keywords:
number cell;
cell;
number;
estimating number ... See more keywords
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Published in 2017 at "Journal of Cheminformatics"
DOI: 10.1186/s13321-017-0208-0
Abstract: BackgroundThe accuracy of any 3D-QSAR, Pharmacophore and 3D-similarity based chemometric target fishing models are highly dependent on a reasonable sample of active conformations. Since a number of diverse conformational sampling algorithm exist, which exhaustively generate…
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Keywords:
representative conformer;
matrix;
clustering algorithms;
conformer ... See more keywords