DocumentCode
260931
Title
Heterogeneous clustering
Author
Charulatha, B.S. ; Rodrigues, Paul ; Chitralekha, T. ; Rajaraman, Arun
fYear
2014
fDate
27-28 Feb. 2014
Firstpage
1
Lastpage
4
Abstract
Web pages now-a-days have different forms and types of content. When the web content is considered they are in the form of pictures, video, audio files and text files in different languages. The present study is aimed at this. The content can be multilingual and heterogeneous. The content of the web is considered as images. Statistical features of the images are extracted. The extracted features are presented to the FCM and subtractive clustering, with similarity metric being Euclidean distance. The accuracy is compared.
Keywords
Internet; feature extraction; pattern clustering; Euclidean distance; FCM; Web content; fuzzy C-means clustering; heterogeneous clustering; similarity metric; statistical feature extraction; subtractive clustering; Animals; Data mining; Density measurement; Educational institutions; Euclidean distance; Feature extraction; Web pages; FCM; Statistical features; Web content; content mining; heterogeneous; subtractive clustering;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Communication and Embedded Systems (ICICES), 2014 International Conference on
Conference_Location
Chennai
Print_ISBN
978-1-4799-3835-3
Type
conf
DOI
10.1109/ICICES.2014.7033890
Filename
7033890
Link To Document