Semi-structured Text Information Extraction Based on Boosting Algorithm

A new information extraction method which is based on Boosting algorithm is provided. It can automatically generate a rule based on an training instance. This rule is applied to training set and change the probability distribution on the weights of positive examples. Next instance will be selected from training set based on this distribution. A constraint named mode-match which can describe words that do not accord with lexical rules is provided too. As experiments show, for the texts with simple characters, both recall and precision can be achieved to 100%. Even for the texts with complex characters, the evaluation of F₁ can be achieved to 80%.