DocumentCode :
2830677
Title :
Research on Deep Web sources classification technology
Author :
Zhao, Huilan
Author_Institution :
Dept. of Comput. Sci. & Technol., North China Electr. Power Univ., Baoding, China
Volume :
3
fYear :
2010
fDate :
21-24 May 2010
Abstract :
Searching on the Internet today can be compared to dragging a net across the surface of the ocean. While a great deal may be caught in the net, there is still a wealth of information that is deep, and therefore, missed. Deep Web sources store their content in searchable databases that only produce result dynamically in response to a direct request. In this paper, we proposed an automatic classification algorithm of Deep Web sources based on iterative self-organizing data analysis techniques algorithm (ISODATA) in order to facilitate users to browse this valuable information.
Keywords :
Internet; data analysis; iterative methods; pattern classification; Internet; automatic classification algorithm; deep Web sources classification technology; iterative selforganizing data analysis techniques algorithm; searchable databases; Data mining; Databases; Information retrieval; Internet; Iterative algorithms; Marine technology; Radio control; Sea surface; Search engines; Web pages; Deep Web; ISODATA; characteristics extraction; deep web source; query interface;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Future Computer and Communication (ICFCC), 2010 2nd International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-5821-9
Type :
conf
DOI :
10.1109/ICFCC.2010.5497681
Filename :
5497681
Link To Document :
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