Search Results - challenges in clustering algorithms

A Taxonomy of Machine Learning Clustering Algorithms, Challenges, and Future Realms by Pitafi, Shahneela, Anwar, Toni, Sharif, Zubair

“… The taxonomy of clustering is presented in this review from an applied angle and the compression of some hierarchical and partitional clustering algorithms with various parameters…”
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Short Text Clustering Algorithms, Application and Challenges: A Survey by Ahmed, Majid Hameed, Tiun, Sabrina, Omar, Nazlia, Sani, Nor Samsiah

“… Short text clustering (STC) has become a critical task for automatically grouping various unlabelled texts into meaningful clusters…”
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Data Stream Clustering Algorithms: Challenges and Future Directions by Sunitha, G., Jaswitha

“… In case of data stream clustering most popularly used heuristic is K-means and other algorithms like K-medoids and the popular BIRCH are developed…”
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Survey on vehicular ad hoc networks clustering algorithms: Overview, taxonomy, challenges, and open research issues by Senouci, Oussama, Harous, Saad, Aliouat, Zibouda

“… Accordingly, several clustering algorithms have been proposed for these networks, and different protocols typically focus on various performance metrics…”
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A comprehensive survey of clustering algorithms: State-of-the-art machine learning applications, taxonomy, challenges, and future research prospects by Ezugwu, Absalom E., Ikotun, Abiodun M., Oyelade, Olaide O., Abualigah, Laith, Agushaka, Jeffery O., Eke, Christopher I., Akinyelu, Andronicus A.

“… However, there has been a gradual shift in the choice of clustering methods among domain experts and practitioners alike, which is precipitated by the fact that most traditional clustering algorithms…”
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Clustering in vehicular ad hoc network: Algorithms and challenges by Mukhtaruzzaman, Mohammad, Atiquzzaman, Mohammed

“…•A comprehensive classification of VANET clustering algorithms: strength and weakness…”
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Software Module Clustering: An In-Depth Literature Analysis by Alsarhan, Qusay, Ahmed, Bestoun S., Bures, Miroslav, Zamli, Kamal Zuhairi

“…Software module clustering is an unsupervised learning method used to cluster software entities (e.g…”
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K-means clustering algorithms: A comprehensive review, variants analysis, and advances in the era of big data by Ikotun, Abiodun M., Ezugwu, Absalom E., Abualigah, Laith, Abuhaija, Belal, Heming, Jia

“… However, the K-means algorithm has many challenges that negatively affect its clustering performance…”
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Multi-omic and multi-view clustering algorithms: review and cancer benchmark by Rappoport, Nimrod, Shamir, Ron

“… Clustering multi-omic data has the potential to reveal further systems-level insights, but raises computational and biological challenges…”
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Unsupervised Hyperspectral Microscopic Image Segmentation Using Deep Embedded Clustering Algorithm by Ajay, P., Nagaraj, B., Kumar, R. Arun, Huang, Ruihang, Ananthi, P.

“… An intuitive chemical species map for a lithium ore sample is produced using k-means clustering…”
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Comparative benchmarking of single-cell clustering algorithms for transcriptomic and proteomic data by Yin, Yu-Hang, Wang, Fang, Li, Wei, Liu, Qiaoming, Zhou, Shengming, Zhou, Murong, Jiang, Zhongjun, Yu, Dong-Jun, Wang, Guohua

“…Background Differences in data distribution, feature dimensions, and quality between different single-cell modalities pose challenges for clustering…”
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Clustering Review in Vehicular Ad hoc Networks: Algorithms, Comparisons, Challenges and Solutions by Jabbar, Mays Kareem, Trabelsi, Hafedh

“… The performance of the clustering is also affected by VANET characteristics. This article provides a comprehensive description of VANET clustering algorithms…”
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De Novo Clustering of Long-Read Transcriptome Data Using a Greedy, Quality Value-Based Algorithm by Sahlin, Kristoffer, Medvedev, Paul

“… To address this challenge, we develop isONclust, a clustering algorithm that is greedy (to scale) and makes use of quality values…”
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Distance-based clustering challenges for unbiased benchmarking studies by Thrun, Michael C.

“…: clustering algorithms are limited in their clustering ability in the presence of clusters defining distance-based structures resulting in a biased clustering solution…”
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Multi-view neutrosophic c-means clustering algorithms by Liu, Zhe, Qiu, Haoye, Deveci, Muhammet, Pedrycz, Witold, Siarry, Patrick

“… However, existing multi-view clustering algorithms still encounter challenges since most multi-view data do not exhibit clear cluster boundaries, meaning cluster boundaries may locally overlap…”
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Challenges and Solutions in Clustering Low-Resource Language Social Media Text: An Evaluation Using Unsupervised Algorithms by Hoti, Mërgim H., Rexhepi, Avni, Hoti, Arbër H., Rexha, Blerim

“…) due to limited annotated corpora, linguistic resources, and pre-trained models. This paper addresses the gap in clustering methodologies for such languages by evaluating the performance of three unsupervised algorithms…”
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Robust k-Means-Type Clustering for Noisy Data by Xiao, Xi, Ma, Hailong, Gan, Guojun, Li, Qing, Zhang, Bin, Xia, Shutao

“… However, real data usually contain noise, which poses significant challenges to clustering algorithms…”
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Clustering benchmark datasets exploiting the fundamental clustering problems by Thrun, Michael C., Ultsch, Alfred

“…The Fundamental Clustering Problems Suite (FCPS) offers a variety of clustering challenges that any algorithm should be able to handle given real-world data…”
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ECCT: Efficient Contrastive Clustering via Pseudo-Siamese Vision Transformer and Multi-view Augmentation by Wei, Xing, Hu, Taizhang, Wu, Di, Yang, Fan, Zhao, Chong, Lu, Yang

“… Nevertheless, existing clustering algorithms face challenges in capturing global information and preserving semantic continuity…”
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Issues, Challenges and Tools of Clustering Algorithms by Agarwal, Parul, Alam, M Afshar, Biswas, Ranjit

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