Results 41 to 50 of about 942,452 (277)

K-Means Clustering with Local Distance Privacy

Big Data Mining and Analytics, 2023
With the development of information technology, a mass of data are generated every day. Collecting and analysing these data help service providers improve their services and gain an advantage in the fierce market competition.
Mengmeng Yang, Longxia Huang, Chenghua Tang   +2 more
doaj   +1 more source

Fast k-means algorithm clustering

, 2011
k-means has recently been recognized as one of the best algorithms for clustering unsupervised data. Since k-means depends mainly on distance calculation between all data points and the centers, the time cost will be high when the size of the dataset is ...
Kecman, Vojislav, Li, Qi, Salman, Raied, Strack, Robert, Test, Erik   +4 more
core   +1 more source

Relational Algorithms for k-means Clustering

CoRR, 2020
This paper gives a k-means approximation algorithm that is efficient in the relational algorithms model. This is an algorithm that operates directly on a relational database without performing a join to convert it to a matrix whose rows represent the data points.
Moseley, Benjamin, Pruhs, Kirk, Samadian, Alireza, Wang, Yuyan   +3 more
openaire   +4 more sources

Clustering with Spectral Norm and the k-means Algorithm [PDF]

, 2010
There has been much progress on efficient algorithms for clustering data points generated by a mixture of $k$ probability distributions under the assumption that the means of the distributions are well-separated, i.e., the distance between the means of ...
Kannan, Ravindran, Kumar, Amit
core   +1 more source

Feature Weighting in k-Means Clustering [PDF]

Machine Learning, 2003
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Dharmendra S. Modha, W. Scott Spangler
openaire   +1 more source

PROCESS CHARACTERISTICS ESTIMATION IN WEB APPLICATIONS USING K-MEANS CLUSTERING [PDF]

Научно-технический вестник информационных технологий, механики и оптики, 2020
Subject of Research. The paper presents the study of estimation problem of process characteristics for the particular case of user’s activity prediction in computer online games.
Victor V. Evstratov, Mikhail S. Ananyevskiy   +1 more
doaj   +1 more source

A Improving House Price Clustering Results with K-means through the Implementation of One-hot Encoding Pre-processing Technique

Journal of Applied Informatics and Computing
Basic human needs include a house that serves as a place to live and a shelter from everything. In Indonesia, owning a house is still a challenging aspect due to its high price.
Vicka Rizqi Maulani, Mula Agung Barata, Pelangi Eka Yuwita   +2 more
doaj   +1 more source

Soil data clustering by using K-means and fuzzy K-means algorithm

Telfor Journal, 2016
A problem of soil clustering based on the chemical characteristics of soil, and proper visual representation of the obtained results, is analysed in the paper. To that aim, K-means and fuzzy K-means algorithms are adapted for soil data clustering.
E. Hot, V. Popović-Bugarin
doaj   +1 more source

Patient Data Analysis with the Quantum Clustering Method

Quantum Reports, 2023
Quantum computing is one of the most promising solutions for solving optimization problems in the healthcare world. Quantum computing development aims to light up the execution of a vast and complex set of algorithmic instructions. For its implementation,
Shradha Deshmukh, Bikash K. Behera, Preeti Mulay   +2 more
doaj   +1 more source

Scalable k-Means Clustering via Lightweight Coresets

, 2018
Coresets are compact representations of data sets such that models trained on a coreset are provably competitive with models trained on the full data set. As such, they have been successfully used to scale up clustering models to massive data sets. While
Arthur David, Bachem Olivier, Bertin-Mahieux Thierry, Jiri Matousek, Reddi Sashank J   +4 more
core   +1 more source