Name
Abstract | ||
|---|---|---|
This paper summarizes our approach to the Semeval 2007 shared task on "Classification of Semantic Relations between Nominals". Our overall strategy is to develop machine-learning classifiers making use of a few easily computable and effective features, selected independently for each classifier in wrapper experiments. We train two types of classifiers for each of the seven relations: with and without WordNet information. |
Year | Venue | Keywords |
|---|---|---|
2007 | SemEval@ACL | overall strategy,shared task,wordnet information,semantic relations,wrapper experiment,machine-learning classifier,shallow feature,effective feature,semantic relation |
Field | DocType | Citations |
SemEval,Computer science,Natural language processing,Artificial intelligence,WordNet,Classifier (linguistics),Machine learning | Conference | 5 |
PageRank | References | Authors |
0.54 | 9 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Iris Hendrickx | 1 | 285 | 30.91 |
| Roser Morante | 2 | 442 | 33.20 |
| Caroline Sporleder | 3 | 453 | 31.84 |
| Antal Van Den Bosch | 4 | 1038 | 132.37 |