Cluster Correspondence Analysis.

Correspondence Clustering: An Approach to Cluster Multiple Related Spatial Datasets

Domain experts are frequently interested to analyze multiple related spatial datasets. This capability is important for change analysis and contrast mining. In this paper, a novel clustering approach called correspondence clustering is introduced that clusters two or more spatial datasets by maximizing cluster interestingness and correspondence between clusters derived from different datasets. ...

Discovering and Analyzing the Intellectual Structure and Its Evolution in Core Journals of "Knowledge and Information Science" during 2004-2013

Purpose: This study aims to reveal the intellectual structure of Knowledge and Information Science and its evolution along with the review of journals subjective scope based on 6830 abstract in the ten core journal in the JCR 2013, over the ten years (2004-2013). Methodology: In this research, co-word and Correspondence analysis of 150 words -selected by tf-idf weight- were done after parametri...

Constraining the correspondence problem by computing correspond- ing regions via a clustering algorithm

Semantic Structure from Correspondence Analysis

A common problem for clustering techniques is that clusters overlap, which makes graphing the statistical structure in the data difficult. A related problem is that we often want to see the distribution of factors (variables) as well as classes (objects). Correspondence Analysis (CA) offers a solution to both these problems. The structure that CA discovers may be an important step in representi...

A Continuum of Consumer Attitudes Toward Genetically Modified Foods in the United States

A national telephone survey was conducted in the United States in April 2002 to study the consumer acceptance of genetically modified (GM) foods. Attitudes toward GM foods were examined through the use of a multiple correspondence analysis (MCA), analyzing the interrelationships among many categorical variables. This method was combined with a cluster analysis to construct a typology of consume...

Pattern Recognition Approach in Multidimensional Databases: Application to the Global Terrorism Database

This paper presents a pattern recognition approach in multidimensional databases. The approach is based on a clustering method using the distance measurement between a reference profile and the database observations. Two distance measurements will be proposed: an adaptation of the Khi formula to the multidimensional context, extracted from the Multiple Correspondence Analysis (MCA), and the Euc...