An Adaptive Smart Crawler for Locating Deep Web Interfaces
Keywords:
Deep web, two-stage crawler, feature selection, ranking, adaptive learning, prequery ,post query.Abstract
As search engine database stores a huge amount of information so searching on the internet is dragging a
net across the surface of the ocean that means everytime it is not possible to get relevant information related with our
query entered in the search engine. As there is a huge amount of information most of the information is hidden, burried
far down on dynamically generated sites and standard search engine fails to find it. Traditional search engine create
indices by crawling it is necessary that the page should be static. Such static pages has been discovered by search engine
as, dynamically generated pages cannot be discovered which results in an increment of hidden data. So it is necessary to
use a two-stage framework for efficient harvesting a deep web and which will also avoid to visit large number of page
