http://www.cnr.it/ontology/cnr/individuo/prodotto/ID180325
Exploiting Structural Similarity for Effective Web Information Extraction (Articolo in rivista)
- Type
- Label
- Exploiting Structural Similarity for Effective Web Information Extraction (Articolo in rivista) (literal)
- Anno
- 2007-01-01T00:00:00+01:00 (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
- 10.1016/j.datak.2006.01.001 (literal)
- Alternative label
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
- Sergio Flesca; Giuseppe Manco; Elio Masciari; Luigi Pontieri; Andrea Pugliese (literal)
- Pagina inizio
- Pagina fine
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
- Rivista
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#pagineTotali
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroFascicolo
- Note
- Google Scholar (literal)
- Elsevier (literal)
- DBLP (literal)
- ISI Web of Science (WOS) (literal)
- Scopu (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
- DEIS, Università della Calabria; ICAR-CNR; ICAR-CNR; ICAR-CNR; DEIS, Università della Calabria (literal)
- Titolo
- Exploiting Structural Similarity for Effective Web Information Extraction (literal)
- Abstract
- In this paper, we propose a classification technique for Web pages, based on the detection of structural similarities among semistructured documents, and devise an architecture exploiting such technique for the purpose of information extraction. The proposal significantly differs from standard methods based on graph-matching algorithms, and is based on the idea of representing the structure of a document as a time series in which each occurrence of a tag corresponds to an impulse. The degree of similarity between documents is then stated by analyzing the frequencies of the corresponding Fourier transform. Experiments on real data show the effectiveness of the proposed technique. (literal)
- Prodotto di
- Autore CNR
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