Title
Dimensionality reduction techniques for blog visualization
Abstract
Exploratory data analysis often relies heavily on visual methods because of the power of the human eye to detect structures. For large, multidimensional data sets which cannot be easily visualized, the number of dimensions of the data can be reduced by applying dimensionality reduction techniques. This paper reviews current linear and nonlinear dimensionality reduction techniques in the context of data visualization. The dimensionality reduction techniques were used in our case study of business blogs. The superior techniques were able to discriminate the various categories of blogs quite accurately. To our knowledge, this is the first study using dimensionality reduction techniques for visualization of blogs. In summary, we have applied dimensionality reduction for visualization of real-world blog data, with potential applications in the ever-growing digital realm of social media.
Year
DOI
Venue
2011
10.1016/j.eswa.2010.08.067
Expert Syst. Appl.
Keywords
Field
DocType
weblog,exploratory data analysis,blog visualization,data visualization,multidimensional data set,visualization,case study,manifold,business blogs,ever-growing digital realm,dimensionality reduction technique,locally linear embedding,multidimensional scaling,isomap,dimensionality reduction,nonlinear dimensionality reduction technique,blog,real-world blog data,nonlinear dimensionality reduction,social media
Data mining,Data visualization,Data set,Dimensionality reduction,Multidimensional scaling,Visualization,Computer science,Artificial intelligence,Exploratory data analysis,Nonlinear dimensionality reduction,Machine learning,Isomap
Journal
Volume
Issue
ISSN
38
3
Expert Systems With Applications
Citations 
PageRank 
References 
15
0.75
12
Authors
1
Name
Order
Citations
PageRank
Flora S. Tsai135223.96