Now showing items 1-6 of 6
Representações distribuídas de texto aplicadas em análise de sentimento de mensagens curtas e ruidosas
(Universidade Federal de São Carlos, 2018-12-14)
The evolution of the Internet and the Web has given rise to a vast amount of text messages containing opinions. Although the importance of sentiment analysis has grown proportionately, the use of the traditional bag of ...
Normalização textual e indexação semântica aplicadas da filtragem de SMS spam
(Universidade Federal de São Carlos, 2016-07-01)
The rapid popularization of smartphones has contributed to the growth of SMS usage as an alternative way of communication. The increasing number of users, along with the trust they inherently have in their devices, makes ...
Filtragem automática de opiniões falsas: comparação compreensiva dos métodos baseados em conteúdo
(Universidade Federal de São Carlos, 2017-08-04)
Before buying a product or choosing for a trip destination, people often seek other people’s opinions to obtain a vision of the quality of what they want to acquire. Given that, opinions always had great influence on the ...
TubeSpam: filtragem automática de comentários indesejados postados no YouTube
(Universidade Federal de São Carlos, 2017-02-03)
YouTube has become an important video sharing platform. Several users regularly produce video content and make this task their main livelihood. However, such success is also drawing the attention of malicious users propagating ...
Aprendiz de descritores de mistura gaussiana
(Universidade Federal de São Carlos, 2017-12-14)
For the last decades, many Machine Learning methods have been proposed aiming categorizing data. Given many tentative models, those methods try to find the one that fits the dataset by building a hypothesis that predicts ...
Aumentando o poder preditivo de classificadores lineares através de particionamento por classe
(Universidade Federal de São Carlos, 2018-01-25)
This work describes a new classification technique called P2C - Partitioning to Classify. The main goal is to achieve reasonable classification performances using linear prediction methods, even on datasets with non-linear ...