Design of Automatically Adaptable Web WrappersEmilioFerraraauthorRobertBaumgartnerauthorNowadays, the huge amount of information distributed through the Web motivates studying techniques to
be adopted in order to extract relevant data in an efficient and reliable way. Both academia and enterprises
developed several approaches of Web data extraction, for example using techniques of artificial intelligence or
machine learning. Some commonly adopted procedures, namely wrappers, ensure a high degree of precision
of information extracted from Web pages, and, at the same time, have to prove robustness in order not to
compromise quality and reliability of data themselves.
In this paper we focus on some experimental aspects related to the robustness of the data extraction process
and the possibility of automatically adapting wrappers. We discuss the implementation of algorithms for
finding similarities between two different version of a Web page, in order to handle modifications, avoiding
the failure of data extraction tasks and ensuring reliability of information extracted. Our purpose is to evaluate
performances, advantages and draw-backs of our novel system of automatic wrapper adaptation.Artificial Intelligence2011Conference Paper