Deep web performance enhance on search engine

Author(s):  
Deepak Kumar ◽  
Rajesh Mishra
2011 ◽  
Vol 50-51 ◽  
pp. 644-648
Author(s):  
Xiao Qing Zhou ◽  
Xiao Ping Tang

The traditional search engine is unable to correct search for the magnanimous information in Deep Web hides. The Web database's classification is the key step which integrates with the Web database classification and retrieves. This article has proposed one kind of classification based on machine learning's web database. The experiment has indicated that after this taxonomic approach undergoes few sample training, it can achieve the very good classified effect, and along with training sample's increase, this classifier's performance maintains stable and the rate of accuracy and the recalling rate fluctuate in the very small scope.


2012 ◽  
Vol 220-223 ◽  
pp. 2920-2923
Author(s):  
Jia Qiang Dong

The Web database's classification is the key step which integrates with the Web database classification and retrieves. The traditional search engine is unable to correct search for the magnanimous information in Deep Web hides. This article has proposed one kind of classification based on machine learning's web database. The experiment has indicated that after this taxonomic approach undergoes few sample training, it can achieve the very good classified effect, and along with training sample's increase, this classifier's performance maintains stable and the rate of accuracy and the recalling rate fluctuate in the very small scope.


2013 ◽  
Vol 397-400 ◽  
pp. 2367-2370
Author(s):  
Xiao Qing Zhou ◽  
Jia Xiu Sun ◽  
Shu Bin Wang

The traditional search engine is unable to correct search for the magnanimous information in Deep Web hides. The Web database's classification is the key step which integrates with the Web database classification and retrieves. This article has proposed one kind of classification based on machine learning's web database. The experiment has indicated that after this taxonomic approach undergoes few sample training, it can achieve the very good classified effect, and along with training sample's increase, this classifier's performance maintains stable and the rate of accuracy and the recalling rate fluctuate in the very small scope.


2004 ◽  
pp. 1313-1316 ◽  
Author(s):  
J GRAUPMANN ◽  
M BIWER ◽  
C ZIMMER ◽  
P ZIMMER ◽  
M BENDER ◽  
...  

Author(s):  
Hadrian Peter ◽  
Charles Greenidge

Traditionally a great deal of research has been devoted to data extraction on the web (Crescenzi, et al, 2001; Embley, et al, 2005; Laender, et al, 2002; Hammer, et al, 1997; Ribeiro-Neto, et al, 1999; Huck, et al, 1998; Wang & Lochovsky, 2002, 2003) from areas where data is easily indexed and extracted by a Search Engine, the so-called Surface Web. There are, however, other sites that are greater and potentially more vital, that contain information which cannot be readily indexed by standard search engines. These sites which have been designed to require some level of direct human participation (for example, to issue queries rather than simply follow hyperlinks) cannot be handled using the simple link traversal techniques used by many web crawlers (Rappaport, 2000; Cho & Garcia-Molina, 2000; Cho et al, 1998; Edwards et al, 2001). This area of the web, which has been operationally off-limits for crawlers using standard indexing procedures, is termed the Deep Web (Zillman, 2005; Bergman, 2000). Much work still needs to be done as Deep Web sites represent an area that is only recently being explored to identify where potential uses can be developed.


2018 ◽  
Vol 5 (1) ◽  
pp. 205395171876862 ◽  
Author(s):  
Richard Rogers

With Google marking its 20th year online, the piece provides a retrospective of cultural commentary and select works of Google art that have transformed the search engine into an object of critical interest. Taken up are artistic and cultural responses to Google by independent artists but also by cultural critics and technology writers, including the development of such evocative notions as the deep web, flickering man and filter bubble. Among the critiques that have taken shape in the works to be discussed here are objects and subjects brought into being by Google (such as ‘spammy neighbourhoods’), Googlization, Google’s information politics, its licensing (or what one is agreeing to when searching) as well as issues surrounding specific products such as Google Street View, as Google leaves the web, capturing more spaces to search.


2003 ◽  
Vol 62 (2) ◽  
pp. 121-129 ◽  
Author(s):  
Astrid Schütz ◽  
Franz Machilek

Research on personal home pages is still rare. Many studies to date are exploratory, and the problem of drawing a sample that reflects the variety of existing home pages has not yet been solved. The present paper discusses sampling strategies and suggests a strategy based on the results retrieved by a search engine. This approach is used to draw a sample of 229 personal home pages that portray private identities. Findings on age and sex of the owners and elements characterizing the sites are reported.


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