Legal information extraction ← machine learning algorithms + linguistic information
| dc.contributor.author | Quaresma, Paulo | |
| dc.date.accessioned | 2013-01-30T00:14:34Z | |
| dc.date.available | 2013-01-30T00:14:34Z | |
| dc.date.issued | 2012-05 | |
| dc.description.abstract | In order to automatically extract information from legal texts we propose the use of a mixed approach, using linguistic information and machine learning techniques. In the proposed architecture, lexical, syntactical, and semantical information is used as input for specialized machine learning algorithms, such as, support vector machines. This approach was applied to collections of legal documents and the preliminary results were quite promising. | por |
| dc.identifier.authoremail | pq@di.uevora.pt | |
| dc.identifier.scientificarea | 283 | por |
| dc.identifier.uri | http://hdl.handle.net/10174/7960 | |
| dc.language.iso | por | por |
| dc.peerreviewed | yes | por |
| dc.publisher | LREC | por |
| dc.rights | restrictedAccess | por |
| dc.title | Legal information extraction ← machine learning algorithms + linguistic information | por |
| dc.type | article | por |