DocumentCode
1796334
Title
Quantum clustering — A novel method for text analysis
Author
Ding Liu ; Minghu Jiang ; Xiaofang Yang
Author_Institution
Sch. of Comput. Sci. & Software Eng., Tianjin Polytech. Univ., Tianjin, China
fYear
2014
fDate
9-12 Dec. 2014
Firstpage
17
Lastpage
23
Abstract
The article introduces quantum clustering inspired from the quantum mechanics and extended to text analysis. This novel method upgrades the nonparametric density estimation and, different from the latter, quantum clustering constructs the potential function to determine the cluster center instead of the Gaussian kernel function. The result of a comparative experiment proves the advantage of quantum clustering over the conventional Parzen-window, and the further trial on authorship identification illustrates the wide application scope of this novel method.
Keywords
estimation theory; nonparametric statistics; pattern clustering; text analysis; authorship identification; nonparametric density estimation; quantum clustering; quantum mechanics; text analysis; Clustering algorithms; Educational institutions; Electric potential; Equations; Kernel; Mathematical model; Quantum mechanics;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence and Data Mining (CIDM), 2014 IEEE Symposium on
Conference_Location
Orlando, FL
Type
conf
DOI
10.1109/CIDM.2014.7008143
Filename
7008143
Link To Document