The Recognizing Textual Entailment System shown here is based on the use of a broad-coverage parser to extract dependency relationships; in addition, WordNet relations are used to ...
The performance of Artificial Neural Networks is largely influenced by the value of their parameters. Among these free parameters, one can mention those related with the network a...
We describe two probabilistic models for unsupervised word-sense disambiguation using parallel corpora. The first model, which we call the Sense model, builds on the work of Diab ...
Semi-supervised clustering uses a small amount of supervised data to aid unsupervised learning. One typical approach specifies a limited number of must-link and cannotlink constra...
In order to deal with the need of sharing learning objects within and across learning object repositories most of the recent work argue for the use of ontologies as a means for pro...