title: Design of Automatically Adaptable Web Wrappers
creator: Ferrara, Emilio
creator: Baumgartner, Robert
subject: Artificial Intelligence
description: Nowadays, 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.
date: 2011
type: Conference Paper
type: PeerReviewed
format: application/pdf
identifier: http://cogprints.org/7640/1/cr-icaart2011.pdf
identifier:   Ferrara, Emilio and Baumgartner, Robert  (2011) Design of Automatically Adaptable Web Wrappers.  [Conference Paper]     
relation: http://cogprints.org/7640/