Extracting keywords for text classification
The article focuses on the TF-IDF matrix construction for text classification into predefined categories. The author describes a tokenization process to reduce the number of unique terms and to extract keywords: lemmatization, stemming, removing of stop words (including specific terms of dataset). As an example, the author constructs a matrix using a dataset of russian texts labeled according to the categories of the online media and a list of 5 keywords for each category.