RED: Redundancy-driven data extraction from result pages?
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 conta...
| Main Authors: | , , , , |
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| Format: | Conference item |
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Association for Computing Machinery
2019
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| _version_ | 1826257955522084864 |
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| author | Guo, J Crescenzi, V Furche, T Grasso, G Gottlob, G |
| author_facet | Guo, J Crescenzi, V Furche, T Grasso, G Gottlob, G |
| author_sort | Guo, J |
| collection | OXFORD |
| description | 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. |
| first_indexed | 2024-03-06T18:26:23Z |
| format | Conference item |
| id | oxford-uuid:081daa4a-01f9-430d-8d04-bf35226d72c2 |
| institution | University of Oxford |
| last_indexed | 2024-03-06T18:26:23Z |
| publishDate | 2019 |
| publisher | Association for Computing Machinery |
| record_format | dspace |
| spelling | oxford-uuid:081daa4a-01f9-430d-8d04-bf35226d72c22022-03-26T09:11:15ZRED: Redundancy-driven data extraction from result pages?Conference itemhttp://purl.org/coar/resource_type/c_5794uuid:081daa4a-01f9-430d-8d04-bf35226d72c2Symplectic Elements at OxfordAssociation for Computing Machinery2019Guo, JCrescenzi, VFurche, TGrasso, GGottlob, GData-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. |
| spellingShingle | Guo, J Crescenzi, V Furche, T Grasso, G Gottlob, G RED: Redundancy-driven data extraction from result pages? |
| title | RED: Redundancy-driven data extraction from result pages? |
| title_full | RED: Redundancy-driven data extraction from result pages? |
| title_fullStr | RED: Redundancy-driven data extraction from result pages? |
| title_full_unstemmed | RED: Redundancy-driven data extraction from result pages? |
| title_short | RED: Redundancy-driven data extraction from result pages? |
| title_sort | red redundancy driven data extraction from result pages |
| work_keys_str_mv | AT guoj redredundancydrivendataextractionfromresultpages AT crescenziv redredundancydrivendataextractionfromresultpages AT furchet redredundancydrivendataextractionfromresultpages AT grassog redredundancydrivendataextractionfromresultpages AT gottlobg redredundancydrivendataextractionfromresultpages |