DocumentCode
176861
Title
PPC:A novel approach of Chinese text mining based on Projection pursuit model
Author
Xinqing Geng ; Zongmin Ma
Author_Institution
Coll. of Math. & Inf. Sci., Anshan Normal Univ., Anshan, China
fYear
2014
fDate
29-30 Sept. 2014
Firstpage
950
Lastpage
952
Abstract
A new fuzzy clustering algorithm (PPC) based on project pursuit model is presented in the paper. The main defect of the traditional clustering algorithm is to reduce dimension, while PPC don´t need reduce dimension. Firstly, the text vector is normalized; Secondly, the project index function is constructed; Thirdly, the project function is optimized; Finally, the clustering result is acquired according to classification threshold. PPC algorithm improves the efficiency and precision of clustering.
Keywords
data mining; fuzzy set theory; pattern classification; pattern clustering; text analysis; vectors; Chinese text mining; PPC; classification threshold; fuzzy clustering algorithm; project index function; projection pursuit model; text vector normalization; Algorithm design and analysis; Classification algorithms; Clustering algorithms; Educational institutions; Indexes; Magnetic heads; Vectors; data mining; projection pursuit model; text clustering;
fLanguage
English
Publisher
ieee
Conference_Titel
Advanced Research and Technology in Industry Applications (WARTIA), 2014 IEEE Workshop on
Conference_Location
Ottawa, ON
Type
conf
DOI
10.1109/WARTIA.2014.6976431
Filename
6976431
Link To Document