Name
Abstract | ||
|---|---|---|
Relation extraction is a key step to address the problem of structuring natural language text. This paper proposes a new ontology class hierarchy feature to improve relation extraction when applying a method based on the distant supervision approach. It argues in favour of the expressiveness of the feature, in multi-class perceptrons, by experimentally showing its effectiveness when compared with combinations of (regular) lexical features. |
Year | Venue | Field |
|---|---|---|
2015 | WISE | Data mining,Ontology,Computer science,Semantic Web,Class hierarchy,Natural language,Structuring,Perceptron,Relationship extraction,Expressivity |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
8 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Pedro H. R. Assis | 1 | 2 | 0.73 |
| Marco A. Casanova | 2 | 1007 | 979.09 |
| Laender Alberto H. F. | 3 | 1920 | 200.88 |
| Ruy Luiz Milidiú | 4 | 192 | 20.18 |