clus·ter

(klŭs′tər)

1. A group of the same or similar elements gathered or occurring closely together; a bunch: "She held out her hand, a small tight cluster of fingers" (Anne Tyler).

2. Linguistics Two or more successive consonants in a word, as cl and st in the word cluster.

3. A group of academic courses in a related area.

v. clus·tered, clus·ter·ing, clus·ters

v.intr.

To gather or grow into bunches.

v.tr.

To cause to grow or form into bunches.

[Middle English, from Old English clyster.]

American Heritage® Dictionary of the English Language, Fifth Edition. Copyright © 2016 by Houghton Mifflin Harcourt Publishing Company. Published by Houghton Mifflin Harcourt Publishing Company. All rights reserved.

Clustering

a group gathered together in a cluster.

Examples: clustering of calamities, 1576; of humble dwellings, 1858; of verdure, 1842; clustering together in companies, 1541.

ThesaurusAntonymsRelated WordsSynonymsLegend:

Noun

clustering - a grouping of a number of similar things; "a bunch of trees"; "a cluster of admirers"

bunch, clump, cluster

agglomeration - a jumbled collection or mass

knot - a tight cluster of people or things; "a small knot of women listened to his sermon"; "the bird had a knot of feathers forming a crest"

swad - a bunch; "a thick swad of plants"

tuft, tussock - a bunch of hair or feathers or growing grass

Translations

clustering

Mentioned in

References in periodicals archive

3(a) and 3(b) show the stability performance of Lowest-ID based 1-hop clustering, Highest-degree based 1-hop clustering, MOBIC based 1-hop clustering, MobDHop based 2-hop clustering, and DWCM based 2-hop clustering when the number of vehicles varies from 50 to 75 with a fixed S = 20 m/s and [T.sub.r] = 200 m.

These figures show that multi-hop clustering approaches (e.g., MobDHop and DWCM) form obviously fewer clusters than 1-hop clustering approaches (e.g., Lowest-ID, Highest-Degree, and MOBIC) in the simulation.

Distributed and weighted clustering based on d-hop dominating set for vehicular networks

Existing research works have proposed the use of hard clustering and fuzzy based approaches for clustering the vehicles.

Rough set based fuzzy scheme for clustering and cluster head selection in VANET

proposed LEACH (Low-Energy Adaptive Clustering Hierarchy) in which sensors have a probability of becoming a cluster head without message exchange [1].

Securing cluster formation and cluster head elections in wireless sensor networks

Clustering is an important technique of exploratory data mining, which divides a set of objects into several groups in such a way that objects in same group are more similar with each other in some sense than with the objects in other groups.

High dimensional data partitioning with an adaptive ensemble construction and analysis scheme

Results show that the K-Means cluster obtains a best cluster "quality" with higher S-KL indexes on the whole and continuous seismic clustering areas.

K-Means Cluster for Seismicity Partitioning and Geological Structure Interpretation, with Application to the Yongshaba Mine (China)

Key words: Data clustering, Partitioned-based clustering algorithms, K-means, Initial centroids.

AN AVERAGE-BASED APPROACH FOR INITIAL CENTROID SELECTION IN K-MEANS ALGORITHM

The proposed algorithm utilizes the fuzzy C-means (FCM) clustering algorithm to automatically identify the damaged area and also combines the TV model to realize image automatic inpainting.

An automatic image inpainting algorithm based on FCM