scholarly journals A machine learning approach to literary genre classification on Portuguese texts: circumventing NLP’s standard varieties

2021 ◽  
Author(s):  
Dionéia Motta Monte-Serrat ◽  
Mateus Tarcinalli Machado ◽  
Evandro Eduardo Seron Ruiz
Keyword(s):  
Machine Learning ◽  
Literary Genre ◽  
Learning Approach ◽  
Genre Classification ◽  
Machine Learning Approach

Avaliamos e classificamos quali-quantitativamente gêneros literários do corpus BDCamões. Crônicas, romances, histórias curtas e contos, anotados em UD, são classificados por florestas aleatórias, e analisados com base na versão português-brasileira do LIWC. Os resultados por classe são reportados pela média, juntamente com uma medida de desvio padrão. Os resultados das características por classe, rótulos LIWC, classes gramaticais e rótulos UD destacam características positivas altas e negativas baixas. A adaptação desta metodologia à fluidez e mutabilidade dos gêneros literários contorna as dificuldade normalemnet encontradas em NLP, apresentando consistência e poucos erros nos resultados.

Bangla Music Genre Classification

2012 ◽  
pp. 124-138
Author(s):  
Ashfaqur Rahman
Keyword(s):  
Machine Learning ◽  
Folk Song ◽  
Learning Approach ◽  
Pop Music ◽  
Classification Framework ◽  
The People ◽  
Genre Classification ◽  
Machine Learning Approach ◽  
Ancient Times ◽  
Music Genre Classification

Bangladesh is very rich in its musical history. Music documented the lives of the people from the ancient times. This chapter provides a guideline for classifying Bangla songs into different genres using a machine learning approach. Four different genres, namely Rabindrasangit, Folk song, Adhunik song, and Pop music, were used in the experiments. A set of second order features are used for representing the trend of change of primary features computed over the timeline of the song. The features are incorporated into a number of classification algorithms and a classification framework is developed. The uniqueness of the genres is clearly revealed by high classification accuracies achieved by the different classifiers.

1552-P: Machine Learning Approach to Decision-Making for Initial Insulin Use in Japanese Patients with Type 2 Diabetes

Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 1552-P
Author(s):  
KAZUYA FUJIHARA ◽  
MAYUKO H. YAMADA ◽  
YASUHIRO MATSUBAYASHI ◽  
MASAHIKO YAMAMOTO ◽  
TOSHIHIRO IIZUKA ◽  
...  
Keyword(s):  
Machine Learning ◽  
Type 2 Diabetes ◽  
Decision Making ◽  
Japanese Patients ◽  
Learning Approach ◽  
Machine Learning Approach ◽  
Insulin Use

A Machine Learning Approach to Jet-Surface Interaction Noise Modeling

2020 ◽  
Author(s):  
Clifford A. Brown ◽  
Jonny Dowdall ◽  
Brian Whiteaker ◽  
Lauren McIntyre
Keyword(s):  
Machine Learning ◽  
Surface Interaction ◽  
Learning Approach ◽  
Noise Modeling ◽  
Machine Learning Approach
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