Clustering is a grouping of devices or other components, typically used for performance enhancement. Clustering computers to execute a single application speeds up the operation of the application.
A feature of the Framework Programmes, the cluster is a defined group of RTD projects. The aim is to guarantee complementarity among projects, to maximise European added value within a given field and to establish a critical mass of resources at the European level.
An unsupervised partitioning of objects into groups whose members are similar in some way. The objects can be genes, experiments, or both.
A closely grouped series of events or cases of a disease or other health-related phenomena with well-defined distribution patterns in relation to time or place or both. The term is normally used to describe aggregation of relatively uncommon events or diseases, e.g., plague, smallpox.
Identifying similar characteristics and grouping samples with similar characteristics together.
Clustering is the grouping of two or more parishes served by one or more priests. The parishes retain their separate identities, but collaborate in the sharing of ministries and resources.
a grouping of a number of similar things; "a bunch of trees"; "a cluster of admirers"
Design principal where ramps are purposefully grouped tightly together in order to increase the number of "lines" that are available. Designs that have equipment that is spaced out often appear to be bigger, however, clustered ramps create better lines and allow for transfers between pieces.
A statistical method of forming natural groupings in which a number of important characteristics of a large diverse group are identified in order to define target markets. For a library such a cluster might include higher education levels, and income. (Wood and Koontz)
The process of grouping competencies into combinations which have meaning and purpose related to work functions and needs in an industry or enterprise. Adapted from Training Package for Assessment and Workplace Training
Grouping similar documents based on their content.
Grouping multiple NAS systems together so that they appear to the end user as a single logical NAS file server.
Locating the presence of groups of vectors that are similar in some fashion.
is grouping information to help children remember it better; a form of brainstorming.
A process of organizing many tasks into groups for the purpose of deciding upon the optimal instructional setting mix for that group of tasks. Also pertains to sequencing groups of objectives within a course of instruction.
Identifying similar characteristics and grouping cases with similar characteristics together.
Group of independent systems working together as a single system. Clustering technology allows groups of servers to access a single disk array containing applications and data.
Clustering is a process of partitioning a set of data into subsets or clusters such that a data element belonging to a cluster is more similar to data elements belonging to the same cluster than the data elements belonging to other clusters.
Certain document collections contain a large number of documents that are only marginally different from other documents. These are often different versions of the same documents or revisions/corrections of one document. These will be grouped together and be presented to the user in a more compact form.
grouping similar items together to form clusters whose centroid or representative characterizes the group
A data mining technique that analyses data to group records together according to their location within the multidimensional attribute space. Clustering is an undirected and unsupervised learning technique.
A data mining function for finding naturally occurring groupings in data. More precisely, given a set of data points, each having a set of attributes, and a similarity measure among them, clustering is the process of grouping the data points into different clusters such that data points in the same cluster are more similar to one another and data points in different clusters are less similar to one another. ODM supports two algorithms for clustering, -means and orthogonal partitioning clustering.
Clustering determines which elements in a dataset are similar. It works to group records together according to an algorithm or mathematical formula that attempts to find centroids, or centers, around which similar records gravitate. It is the process of dividing a dataset into mutually exclusive subgroups, without relying on predefined classes.
The grouping of homesites within a subdivision on less-than normal-sized lots, with the remaining land used as common areas.
In phenetic classification, the conversion of a similarity matrix to a phenogram, by mathematically grouping organisms according to their phenetic similarities.
unsupervised training; the process of generating signatures based on the natural groupings of pixels in image data when they are plotted in spectral space.
A content field technique or strategy to help students freely associate ideas in their experience with a keyword proposed by the teacher, thus forming a group of related concepts; a teaching process of relating a target word to a set of synonyms and other word associations. Note: Clustering may be used to stimulate the recall of related ideas in reading and writing, especially in prewriting.
The process of dividing a dataset into mutually exclusive groups such that the members of each group are as "close" as possible to one another, and different groups are as "far" as possible from one another, where distance is measured with respect to all available variables.
Grouping together of independent cable systems into a larger, more efficient single system that utilizes some of the same infrastructure.
Clustering algorithms find groups of items that are similar. For example, clustering could be used by an insurance company to group customers according to income, age, types of policies purchased and prior claims experience. It divides a data set so that records with similar content are in the same group, and groups are as different as possible from each other. Since the categories are unspecified, this is sometimes referred to as unsupervised learning.