Articles with "clustering algorithms" as a keyword



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A comparison of graph-based word sense induction clustering algorithms in a pseudoword evaluation framework

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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… read more here.

Keywords: word; clustering algorithms; pseudoword; graph ... See more keywords
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Outlier detection using an ensemble of clustering algorithms

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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… read more here.

Keywords: outlier detection; clustering algorithms; using ensemble; detection using ... See more keywords
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An overview of recent multi-view clustering

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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… read more here.

Keywords: view clustering; overview recent; view; clustering algorithms ... See more keywords
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Fundamental clustering algorithms suite

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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… read more here.

Keywords: algorithms suite; fundamental clustering; cluster; clustering algorithms ... See more keywords
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A comparative analysis of clustering algorithms to identify the homogeneous rainfall gauge stations of Bangladesh

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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… read more here.

Keywords: comparative analysis; means clustering; clustering algorithms; rainfall ... See more keywords
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Directed Graph Clustering Algorithms, Topology, and Weak Links

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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… read more here.

Keywords: topology; directed graph; weak links; clustering algorithms ... See more keywords
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Comparison and Analysis of Several Clustering Algorithms for Pavement Crack Segmentation Guided by Computational Intelligence

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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… read more here.

Keywords: crack; pavement crack; clustering algorithms; comparison ... See more keywords
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Application of Clustering Algorithms to TRMM Precipitation over the Tropical and South Pacific Ocean

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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 ... read more here.

Keywords: south pacific; clustering algorithms; algorithms trmm; application clustering ... See more keywords
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A robustness metric for biological data clustering algorithms

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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… read more here.

Keywords: robustness metric; metric biological; clustering algorithms; data clustering ... See more keywords
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Benchmarking clustering algorithms on estimating the number of cell types from single-cell RNA-sequencing data

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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… read more here.

Keywords: number cell; cell; number; estimating number ... See more keywords
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The comparison of automated clustering algorithms for resampling representative conformer ensembles with RMSD matrix

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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… read more here.

Keywords: representative conformer; matrix; clustering algorithms; conformer ... See more keywords