Name
Abstract | ||
|---|---|---|
Many software agents require information that is available in web documents. Unfortunately, the existing proposals to learn extraction rules are tightly coupled with the learning component and do not result in resilient rules. We present a novel approach that leverages neural networks and has proven to be very resilient. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1007/978-3-319-19629-9_15 | TRENDS IN PRACTICAL APPLICATIONS OF AGENTS, MULTI-AGENT SYSTEMS AND SUSTAINABILITY: THE PAAMS COLLECTION |
Keywords | Field | DocType |
Web information extraction,neural networks,resiliency | World Wide Web,Web analytics,Computer science,Software agent,Artificial neural network,Web service,Web information | Conference |
Volume | ISSN | Citations |
372 | 2194-5357 | 1 |
PageRank | References | Authors |
0.34 | 13 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Patricia Jiménez | 1 | 14 | 3.99 |
| Hassan A. Sleiman | 2 | 103 | 8.33 |
| Rafael Corchuelo | 3 | 389 | 49.87 |