This paper is focused on automatic multi-label document classification of Czech text
documents. The current approaches usually use some pre-processing which can have …

We examine the effectiveness of several unsupervised methods for latent semantics
discovery as features for aspect-based sentiment analysis (ABSA). We use the shared task …

In text classification task one of the main problems is to choose which features give the best
results. Various features can be used like words, n-grams, syntactic n-grams of various types …

Book recommendation to support professors and students in the identification of relevant
sources is of significant importance for both universities and digital libraries and, hence …

This paper investigates three different sources of information and their integration into
language modelling. Global semantics is modelled by Latent Dirichlet allocation and brings …

This paper deals with multi-label document classification using an ensemble of neural
networks. The assumption is that different network types can keep complementary …

Abstract Language models are crucial for many tasks in natural language processing and n-
grams are probably the best way to build them. Huge effort is being invested in improving …

Aspects of Sentiment Analysis Page 1 University of West Bohemia Faculty of Applied Sciences
Department of Computer Science and Engineering Aspects of Sentiment Analysis Ing. Tomáš …

This paper deals with automatic document classification in the context of a real application
for the Czech News Agency (ČTK). The accuracy our classifier is high, however it is still …

This paper aims at bridging the gap between feature selection and feature space size by
utilizing both square and non-square self-organizing maps under different configuration …