Data-driven websites are mostly accessed through search interfaces. Such sites follow a common publishing pattern that, surprisingly, has not been fully exploited for unsupervised data extraction yet: the result of a search is presented as a paginated list of result records. Each result record contains the main attributes about one single object, and links to a page dedicated to the details of that object. We present red, an automatic approach and a prototype system for extracting data records from sites following this publishing pattern. red leverages the inherent redundancy between result records and corresponding detail pages to design an effective, yet fully-unsupervised and domain-independent method. It is able to extract from result pages all the attributes of the objects that appear both in the result records and in the corresponding detail pages. With respect to previous unsupervised methods, our method does not require any a priori domain-dependent knowledge (e.g, an ontology), can achieve a significantly higher accuracy while automatically selecting only object attributes, a task which is out of the scope of traditional fully unsupervised approaches. With respect to previous supervised or semi-supervised methods, red can reach similar accuracy in many domains (e.g., job postings) without requiring supervision for each domain, let alone each website.

Red: Redundancy-driven data extraction from result pages

Grasso G.;Gottlob G.
2019

Abstract

Data-driven websites are mostly accessed through search interfaces. Such sites follow a common publishing pattern that, surprisingly, has not been fully exploited for unsupervised data extraction yet: the result of a search is presented as a paginated list of result records. Each result record contains the main attributes about one single object, and links to a page dedicated to the details of that object. We present red, an automatic approach and a prototype system for extracting data records from sites following this publishing pattern. red leverages the inherent redundancy between result records and corresponding detail pages to design an effective, yet fully-unsupervised and domain-independent method. It is able to extract from result pages all the attributes of the objects that appear both in the result records and in the corresponding detail pages. With respect to previous unsupervised methods, our method does not require any a priori domain-dependent knowledge (e.g, an ontology), can achieve a significantly higher accuracy while automatically selecting only object attributes, a task which is out of the scope of traditional fully unsupervised approaches. With respect to previous supervised or semi-supervised methods, red can reach similar accuracy in many domains (e.g., job postings) without requiring supervision for each domain, let alone each website.
9781450366748
Automatic Wrapper Generation; Web Data Extraction; XPath
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.11770/302901
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 3
  • ???jsp.display-item.citation.isi??? 2
social impact