DocumentCode
3082049
Title
Customized Category Based Clustering of URLs
Author
Anand, Nitin
Author_Institution
Dept. of Comput. Sci., Maharaja Surajmal Inst., New Delhi, India
fYear
2013
fDate
24-26 Aug. 2013
Firstpage
310
Lastpage
314
Abstract
Web applications are taking popularity in number of ways. Monitoring the client side data allow for gathering valuable information about its behaviour. In this paper an intelligent and integrated system for user activity monitoring for both computer and internet movement is proposed. The system provides on-line and off-line monitoring and allows detecting user behaviour. On-line monitoring is carried in real time and is used to predict user actions. Off-line monitoring is carried out after user has ended his work, and is based on the analysis of statistical parameters of user behaviour. A method for the identifying the category of web sites is also presented. Our system performs clustering on the basis of URL. The URL clustering is very informative, making techniques based on it faster than that make use of text information as well.
Keywords
Internet; Web sites; human computer interaction; human factors; pattern clustering; statistical analysis; user interfaces; Internet movement; URL; Web sites; World Wide Web service; behaviour detection; category identification; client side data monitoring; computer movement; customized category based clustering; intelligent system; k-means clustering; offline monitoring; online monitoring; statistical parameters analysis; uniform resource locator; user action prediction; user activity monitoring; valuable information gathering; Clustering algorithms; Computers; Data mining; Internet; Monitoring; Navigation; Web pages; Clustering; Domain Name; K-means clustering; Monitoring; URL;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational and Business Intelligence (ISCBI), 2013 International Symposium on
Conference_Location
New Delhi
Print_ISBN
978-0-7695-5066-4
Type
conf
DOI
10.1109/ISCBI.2013.68
Filename
6724374
Link To Document