The article discusses how text classification can help quickly find information in large amounts of text. The researchers created a text classifier for architecture using the TF-IDF method for feature selection. They compared Naive Bayes, KNN, and decision tree classifiers, finding that Naive Bayes had the best performance in predicting results. The Naive Bayes classifier can improve the accuracy and recall rate of text classification in architecture.