A Deep Learning Method Study of User Interest Classification

P. 154–159.

Malafeev A., Nikolaev K.

In this paper, a deep learning method study is conducted to solve a new multiclass text classification problem, identifying user interests by text messages. We used an original dataset of almost 90 thousand forum text messages, labeled for ten interests. We experimented with different modern neural network architectures: recurrent and convolutional, as well as simpler feedforward networks. Classification accuracy was evaluated for different architectures, text representations, and sets of miscellaneous parameters.

Keywords: машинное обучение, нейронные сети, neural networks, machine learning, классификация текстов, deep learning, convolutional neural networks, text classification, сверточные нейронные сети, глубокое обучение, user interests, feedforward neural networks, long short term memory, интересы пользователей, нейронные сети с прямой связью, долгосрочная кратковременная память

Publication based on the results of: Эффективные методы распознавания мультимедийных данных для задач анализа предпочтений пользователей мобильных устройств (2019)

In book

Analysis of Images, Social Networks and Texts. 8th International Conference, AIST 2019, Kazan, Russia, July 17–19, 2019, Revised Selected Papers. Communications in Computer and Information Science

Vol. 1086. , Springer, 2020.