Using XPaths of Inbound Links to Cluster Template-Generated Web Pages.
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| Title: | Using XPaths of Inbound Links to Cluster Template-Generated Web Pages. |
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| Authors: | Grigalis, Tomas1 tomas.grigalis@vgtu.lt, Čenys, Antanas1 antanas.cenys@vgtu.lt |
| Source: | Computer Science & Information Systems. Jan2014, Vol. 11 Issue 1, p111-131. 21p. |
| Subjects: | Websites, XPath (Computer program language), Programming languages, Electronic file management, Document clustering, Data extraction |
| Abstract: | Template-generated Web pages contain most of structured data on the Web. Clustering these pages according to their template structure is an important problem in wrapper-based structured data extraction systems. These systems extract structured data using wrappers that must be matched to only particular template pages. Selecting single type of template from all crawled Web pages is a time consuming task. Although there are methods to cluster Web pages according to their structural similarity, however, in most cases they are too computationally expensive to be applicable at Web-Scale. We propose a novel highly scalable approach to structurally cluster Web pages by employing XPath addresses of inbound inner-site links. We demonstrate the effectiveness of our method by clustering more than one million Web pages from many real world Websites in a few minutes and achieving >90% accuracy. [ABSTRACT FROM AUTHOR] |
| Copyright of Computer Science & Information Systems is the property of ComSIS Consortium and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 94899408 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Using XPaths of Inbound Links to Cluster Template-Generated Web Pages. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Grigalis%2C+Tomas%22">Grigalis, Tomas</searchLink><relatesTo>1</relatesTo><i> tomas.grigalis@vgtu.lt</i><br /><searchLink fieldCode="AR" term="%22Čenys%2C+Antanas%22">Čenys, Antanas</searchLink><relatesTo>1</relatesTo><i> antanas.cenys@vgtu.lt</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Computer+Science+%26+Information+Systems%22">Computer Science & Information Systems</searchLink>. Jan2014, Vol. 11 Issue 1, p111-131. 21p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Websites%22">Websites</searchLink><br /><searchLink fieldCode="DE" term="%22XPath+%28Computer+program+language%29%22">XPath (Computer program language)</searchLink><br /><searchLink fieldCode="DE" term="%22Programming+languages%22">Programming languages</searchLink><br /><searchLink fieldCode="DE" term="%22Electronic+file+management%22">Electronic file management</searchLink><br /><searchLink fieldCode="DE" term="%22Document+clustering%22">Document clustering</searchLink><br /><searchLink fieldCode="DE" term="%22Data+extraction%22">Data extraction</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Template-generated Web pages contain most of structured data on the Web. Clustering these pages according to their template structure is an important problem in wrapper-based structured data extraction systems. These systems extract structured data using wrappers that must be matched to only particular template pages. Selecting single type of template from all crawled Web pages is a time consuming task. Although there are methods to cluster Web pages according to their structural similarity, however, in most cases they are too computationally expensive to be applicable at Web-Scale. We propose a novel highly scalable approach to structurally cluster Web pages by employing XPath addresses of inbound inner-site links. We demonstrate the effectiveness of our method by clustering more than one million Web pages from many real world Websites in a few minutes and achieving >90% accuracy. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Computer Science & Information Systems is the property of ComSIS Consortium and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.2298/CSIS130416020G Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 21 StartPage: 111 Subjects: – SubjectFull: Websites Type: general – SubjectFull: XPath (Computer program language) Type: general – SubjectFull: Programming languages Type: general – SubjectFull: Electronic file management Type: general – SubjectFull: Document clustering Type: general – SubjectFull: Data extraction Type: general Titles: – TitleFull: Using XPaths of Inbound Links to Cluster Template-Generated Web Pages. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Grigalis, Tomas – PersonEntity: Name: NameFull: Čenys, Antanas IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Text: Jan2014 Type: published Y: 2014 Identifiers: – Type: issn-print Value: 18200214 Numbering: – Type: volume Value: 11 – Type: issue Value: 1 Titles: – TitleFull: Computer Science & Information Systems Type: main |
| ResultId | 1 |
