Evaluating text classifier parameters based on semantic features

摘要

Systems and methods for evaluating text classifier parameters based on semantic features. An example method comprises: performing a semantico-syntactic analysis of a natural language text of a corpus of natural language texts to produce a semantic structure representing a set of semantic classes; identifying a natural language text feature to be extracted using a set of values of a plurality of feature extraction parameters; partitioning the corpus of natural language texts into a training data set comprising a first plurality of natural language texts and a validation data set comprising a second plurality of natural language texts; determining, in view of the category of the training data set, the set of values of the feature extraction parameters; validating the set of values of the feature extraction parameters using the validation data set.