Name
Abstract | ||
|---|---|---|
Many web sites contain large sets of pages generated using a common template or layout. For example, Amazon lays out the author, title, comments, etc. in the same way in all its book pages. The values used to generate the pages (e.g., the author, title,...) typically come from a database. In this paper, we study the problem of automatically extracting the database values from such template-generated web pages without any learning examples or other similar human input. We formally define a template, and propose a model that describes how values are encoded into pages using a template. We present an algorithm that takes, as input, a set of template-generated pages, deduces the unknown template used to generate the pages, and extracts, as output, the values encoded in the pages. Experimental evaluation on a large number of real input page collections indicates that our algorithm correctly extracts data in most cases. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1145/872757.872799 | SIGMOD Conference |
Keywords | Field | DocType |
template-generated page,similar human input,large set,real input page collection,common template,unknown template,large number,template-generated web page,structured data,database value,web page,extracts data,coalescing,web pages,temporal databases,granularity,incomplete information | Static web page,Data mining,HITS algorithm,Information retrieval,Web page,Computer science,Website Parse Template,Temporal database,Data model,Complete information,Database | Conference |
ISBN | Citations | PageRank |
1-58113-634-X | 394 | 16.28 |
References | Authors | |
21 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Arvind Arasu | 1 | 2475 | 141.59 |
| Héctor García-Molina | 2 | 24359 | 5652.13 |
| Stanford University | 3 | 394 | 16.28 |