Name
Abstract | ||
|---|---|---|
Deep Web sites expose data from a database, whose conceptual model remains hidden. Having access to that model is mandatory to perform several tasks, such as integrating different web sites; extracting information from the web unsupervisedly; or creating ontologies. In this paper, we propose a technique to discover the conceptual model behind a web site in the Deep Web, using a statistical approach to discover relationships between entities. Our proposal is unsupervised, not requiring the user to have expert knowledge; and it does not focus on a single view on the database, instead it integrates all views containing entities and relationships that are exposed in the web site. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1007/978-3-642-34002-4_13 | ER |
Keywords | Field | DocType |
statistical approach,single view,conceptual model,web site,deep web,different web site,deep web site,web unsupervisedly,expert knowledge,conceptual models | Data mining,World Wide Web,Web intelligence,Web mining,Semantic Web Stack,Computer science,Web mapping,Web standards,Data Web,Web modeling,Social Semantic Web,Database | Conference |
Citations | PageRank | References |
4 | 0.42 | 16 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Inma Hernández | 1 | 76 | 10.72 |
| Carlos R. Rivero | 2 | 111 | 16.25 |
| David Ruiz | 3 | 152 | 20.62 |
| Rafael Corchuelo | 4 | 389 | 49.87 |