DocumentCode :
2159997
Title :
An approach for accessing data from hidden web using intelligent agent technology
Author :
Singh, Lavneet ; Sharma, D.K.
Author_Institution :
Dept. of CEA, GLA Univ., Mathura, India
fYear :
2013
fDate :
22-23 Feb. 2013
Firstpage :
800
Lastpage :
805
Abstract :
There is large amount of information available on web, which is hidden from users. This is because such information is not able to be accessed or indexed by traditional search engines. These search engines are only able to crawl information by following hypertext links. The forms which require login or any authorization process can be ignored by them. Hidden web refers to that deepest part of the Web which is not available for traditional Web crawlers. Obtaining the content from Hidden web is a challenging task. Today many web sites are containing pages that are dynamic in nature. This dynamic nature of web pages creates a problem for retrieving information for traditional web crawlers. The effort done to solve the given problem is discussed in brief. Then, a comparative study among the earlier defined architecture, considering various parameters, is also shown. By analyzing above methods a framework is proposed which uses an intelligent agent technology for accessing the hidden web.
Keywords :
Web sites; authorisation; hypermedia; indexing; information retrieval; search engines; software agents; Web crawlers; Web sites; authorization process; data access approach; hidden Web; hypertext links; information crawling; information retrieval problem; intelligent agent technology; search engines; Crawlers; Databases; Feature extraction; Filling; Intelligent agents; Learning (artificial intelligence); Search engines; Hidden Web; Hidden Web Crawling; Hidden Web Databases; Intelligent Agent Technology;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advance Computing Conference (IACC), 2013 IEEE 3rd International
Conference_Location :
Ghaziabad
Print_ISBN :
978-1-4673-4527-9
Type :
conf
DOI :
10.1109/IAdCC.2013.6514329
Filename :
6514329
Link To Document :
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