Name
Abstract | ||
|---|---|---|
The Web has been the star service on the Internet, however the outsized information available and its decentralized nature has originated an intrinsic difficulty to locate, extract and compose information. An automatic approach is required to handle with this huge amount of data. In this paper we present a machine learning algorithm based on Genetic Algorithms which generates a set of complex wrappers, able to extract information from the Web. The paper presents the experimental evaluation of these wrappers over a set of basic data sets. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1007/978-3-642-12433-4_44 | TRENDS IN PRACTICAL APPLICATIONS OF AGENTS AND MULTIAGENT SYSTEMS |
Keywords | Field | DocType |
machine learning,genetics,genetic algorithm | Regular expression,Data set,Computer science,Artificial intelligence,Genetic representation,Regular language,Population-based incremental learning,Machine learning,Genetic algorithm,The Internet | Conference |
Volume | ISSN | Citations |
71 | 1867-5662 | 2 |
PageRank | References | Authors |
0.40 | 6 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| David F. Barrero | 1 | 120 | 17.17 |
| Antonio González-Pardo | 2 | 114 | 14.68 |
| María D. R-Moreno | 3 | 97 | 15.22 |
| David Camacho | 4 | 278 | 24.89 |