Authors:Ádám Pintér, Balázs Schmuck, and Sándor Szénási
The aim of this paper is to present a technique, which uses machine learning to process the short text answers with Hungarian language. The processing is based on a special neural network, the convolutional neural network, which can efficiently process short text answer. To achieve precise classification for training and recall grammatically consistent answers and the conversion of the text to the input are inevitable. To convert the input, continuous bag of words and Skip-Gram models will be used, resulting in a model that will be able to evaluate the Hungarian short text answers.