In data-intensive web sites pages are generated by scripts that embed data from a back-end database into HTML templates. There is usually a relationship between the semantics of the data in a page and its corresponding template. For example, in a web site about sports events, it is likely that pages with data about athletes are associated with a template that differs from the template used to generate pages about coaches or referees. This article presents a method to classify web pages according to the associated template. Given a web page, the goal of our method is to accurately find the pages that are about the same topic. Our method leverages on a simple, yet effective model to abstract some structural features of a web page. We present the results of an extensive experimental analysis that show the performance of our methods in terms of both recall and precision regarding a large number of real-world web pages.

LORENZO BLANCO, CRESCENZI V, & PAOLO MERIALDO (2008). Structure and Semantics of Data-IntensiveWeb Pages: An Experimental Study on their Relationships. JOURNAL OF UNIVERSAL COMPUTER SCIENCE, 14, 1877-1892 [10.3217/jucs-014-11-1877].

Structure and Semantics of Data-IntensiveWeb Pages: An Experimental Study on their Relationships

CRESCENZI, VALTER;MERIALDO, PAOLO
2008

Abstract

In data-intensive web sites pages are generated by scripts that embed data from a back-end database into HTML templates. There is usually a relationship between the semantics of the data in a page and its corresponding template. For example, in a web site about sports events, it is likely that pages with data about athletes are associated with a template that differs from the template used to generate pages about coaches or referees. This article presents a method to classify web pages according to the associated template. Given a web page, the goal of our method is to accurately find the pages that are about the same topic. Our method leverages on a simple, yet effective model to abstract some structural features of a web page. We present the results of an extensive experimental analysis that show the performance of our methods in terms of both recall and precision regarding a large number of real-world web pages.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11590/141536
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