Predicting the User Intention in Web Search

Abstract

The search for information is inherent to the human being and with the popularization of computers, search systems have become the main source of obtaining knowledge. However, they do not support greater user interaction when they want to do a complex search. It is important to evaluate the user and infer information about him, to know his intention to search to increase the performance of these systems under the principles of SaL. In this paper, we propose a model for classifying the search intention using Transformers. It was used an available dataset and we obtained 97% accuracy in the validation set and 99% f-measure in the test set, achieving better results when comparing to traditional methods.