Combining Linguistic Features with Weighted Bayesian Classifier for Temporal Reference Processing

Guihong Cao

RALI, DIRO

Le 20 octobre 2004 à 11 h 30

Salle 3195, Pavillon André-Aisenstadt


We will present a computational model for determining temporal relations in Chinese. The model takes into account the effects of linguistic features, such as tense/aspect, temporal connectives, and discourse structures, and makes use of the fact that events are represented in different temporal structures. A machine learning approach, Weighted Bayesian Classifier, is developed to map their combined effects to the corresponding relations. An empirical study is conducted to investigate different combination methods, including lexical-based, grammatical-based, and role-based methods. When used in combination, the weights of the features may not be equal. Incorporating with an optimization algorithm, the weights are fine tuned and the improvement is remarkable.


Pour recevoir les annonces hebdomadaires par courriel, envoyez un message à l'adresse majordomo@iro.umontreal.ca

Liste des autres séminaires