DocumentCode :
2783347
Title :
Entities Identification on the Deep Web Using Neural Network
Author :
Qiang, Baohua ; Wu, Chunming ; Zhang, Long
Author_Institution :
Sch. of Comput. Sci. & Eng., Guilin Univ. of Electron. Technol., Guilin, China
fYear :
2010
fDate :
10-12 Oct. 2010
Firstpage :
476
Lastpage :
479
Abstract :
With the rapid developments and extensive applications of internet, a large number of duplicated entities on the Web, especially on the Deep Web, require to be eliminated and integrated effectively. So identifying the corresponding entities on the Deep Web is critical. Due to the query interface on the HTML page represents the schema of the Web database, we firstly try to obtain the schema of the entities on the Deep Web by extracting the schema of the query interface in order to improve the accuracy for entities matching. Then an entities identification approach on the Deep Web using neural network is proposed. The experimental results show the effectiveness of our proposed algorithm.
Keywords :
Internet; feature extraction; hypermedia markup languages; neural nets; query processing; Deep Web; HTML page; Internet application; Web database; entity identification; entity matching; neural network; query interface; schema extraction; Accuracy; Artificial neural networks; Books; Conferences; Databases; Helium; Training; Deep Web; entities identification; neural network; schema extraciton;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC), 2010 International Conference on
Conference_Location :
Huangshan
Print_ISBN :
978-1-4244-8434-8
Electronic_ISBN :
978-0-7695-4235-5
Type :
conf
DOI :
10.1109/CyberC.2010.93
Filename :
5616990
Link To Document :
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