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Design of Automatically Adaptable Web Wrappers

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Document pages: 7 pages

Abstract: Nowadays, the huge amount of information distributed through the Web motivates studying techniques tobe adopted in order to extract relevant data in an efficient and reliable way. Both academia and enterprisesdeveloped several approaches of Web data extraction, for example using techniques of artificial intelligence ormachine learning. Some commonly adopted procedures, namely wrappers, ensure a high degree of precisionof information extracted from Web pages, and, at the same time, have to prove robustness in order not tocompromise quality and reliability of data themselves.In this paper we focus on some experimental aspects related to the robustness of the data extraction processand the possibility of automatically adapting wrappers. We discuss the implementation of algorithms forfinding similarities between two different version of a Web page, in order to handle modifications, avoidingthe failure of data extraction tasks and ensuring reliability of information extracted. Our purpose is to evaluateperformances, advantages and draw-backs of our novel system of automatic wrapper adaptation.

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