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
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;
Conference_Titel :
Computational Intelligence and Data Mining (CIDM), 2014 IEEE Symposium on
Conference_Location :
Orlando, FL
DOI :
10.1109/CIDM.2014.7008143