Editor/Reviewer loginFrequency : 12 issues per year
Subject : Computer Applications and Technology
ISSN : 2319–8656 (Online)
IJCATR Volume 5 Issue 10
Literature Survey: Clustering Technique
Ajinkya V. Jiman Prof. Harmeet K. Khanuja
10.7753/IJCATR0510.1008
keywords : Clustering, Clustering techniques, Clustering algorithms, Cluster input parameters, Cluster input data type.
Clustering is a partition of data into the groups of similar or dissimilar objects. Clustering is unsupervised learning technique helps to ?nd out hidden patterns of Data Objects. These hidden patterns represent a data concept. Clustering is used in many data mining applications for data analysis by ?nding data patterns. There is a number of clustering techniques and algorithms are available to cluster the data object. According to the type of data object and structure appropriate clustering technique is selected. This survey focuses on the clustering techniques for their input attribute data type, their input parameters and output. The main objective is not to understand the actual working of clustering technique. Instead, the input data requirement and input parameters of clustering technique are focused.
@artical{a5102016ijcatr01101008,
Title = "Literature Survey: Clustering Technique",
Journal ="International Journal of Computer Applications Technology and Research(IJCATR)",
Volume = "5",
Issue ="10",
Pages ="671 - 674",
Year = "2016",
Authors ="Ajinkya V. Jiman
Prof. Harmeet K. Khanuja"}
This research paper provides basic information on clustering, clustering analysis and clustering techniques.
Basic understanding of Data Object and Attribute types.
Provides simple categorization of clustering techniques.
Also, this paper describes required input parameter, required input data object type and output of each clustering technique.