Clustering Web pages based on their structure

Valter Crescenzi, Paolo Merialdo, Paolo Missier

    Research output: Contribution to journalArticlepeer-review

    Abstract

    Several techniques have been recently proposed to automatically generate Web wrappers, i.e., programs that extract data from HTML pages, and transform them into a more structured format, typically in XML. These techniques automatically induce a wrapper from a set of sample pages that share a common HTML template. An open issue, however, is how to collect suitable classes of sample pages to feed the wrapper inducer. Presently, the pages are chosen manually. In this paper, we tackle the problem of automatically discovering the main classes of pages offered by a site by exploring only a small yet representative portion of it. We propose a model to describe abstract structural features of HTML pages. Based on this model, we have developed an algorithm that accepts the URL of an entry point to a target Web site, visits a limited yet representative number of pages, and produces an accurate clustering of pages based on their structure. We have developed a prototype, which has been used to perform experiments on real-life Web sites. © 2004 Elsevier B.V. All rights reserved.
    Original languageEnglish
    Pages (from-to)279-299
    Number of pages20
    JournalData and Knowledge Engineering
    Volume54
    Issue number3
    DOIs
    Publication statusPublished - 2005

    Keywords

    • Clustering
    • Information extraction
    • Web mining
    • Web modelling
    • Wrapper induction

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