Data Extraction from Web Tables: The Devil is in the Details

Author

Nagy, G. ; Seth, Sachin ; Dongpu Jin ; Embley, David W. ; Machado, S. ; Krishnamoorthy, Mohan

Author_Institution

Electr., Comput., & Syst. Eng., Rensselaer Polytech. Inst., Troy, NY, USA

fYear

2011

fDate

18-21 Sept. 2011

Firstpage

242

Lastpage

246

Abstract

We present a method based on header paths for efficient and complete extraction of labeled data from tables meant for humans. Although many table configurations yield to the proposed syntactic analysis, some require access to semantic knowledge. Clicking on one or two critical cells per table, through a simple interface, is sufficient to resolve most of these problem tables. Header paths, a purely syntactic representation of visual tables, can be transformed ("factored") into existing representations of structured data such as category trees, relational tables, and RDF triples. From a random sample of 200 web tables from ten large statistical web sites, we generated 376 relational tables and 34,110 subject-predicate-object RDF triples.

Keywords

Web sites; data mining; semantic Web; Web tables; data extraction; header paths; relational tables; semantic knowledge; statistical Web sites; subject-predicate-object RDF triples; syntactic analysis; syntactic representation; Data mining; Educational institutions; HTML; Indexing; Resource description framework; Web sites; RDF; header-paths; relational table; visual table;

fLanguage

English

Publisher

ieee

Conference_Titel

Document Analysis and Recognition (ICDAR), 2011 International Conference on

Conference_Location

Beijing

ISSN

1520-5363

Print_ISBN

978-1-4577-1350-7

Electronic_ISBN

1520-5363

Type

conf

DOI

10.1109/ICDAR.2011.57

Filename

6065312