In this publication we describe a novel two-dimensional approach for automatic music genre classification. Although the subject poses a well studied task in Music Information Retrieval, some fundamental issues of genre classification have not been covered so far. Especially many modern genres are influenced by manifold musical styles. Most of all, this holds true for the broad category “World M...

Music genres allow to categorize musical items that share common characteristics. Although these categories are not mutually exclusive, most related research is traditionally focused on classifying tracks into a single class. Furthermore, these categories (e.g., Pop, Rock) tend to be too broad for certain applications. In this work we aim to expand this task by categorizing musical items into m...

This paper proposes a movie genreprediction based on multinomial probability model. To the best of our knowledge, this problem has not been addressed yet in the field of recommender system. The prediction of a movies genre has many practical applications including complementing the items categories given by experts and providing a surprise effect in the recommendations given to a user. We emplo...

This paper describes the participation between the LIDIC research group of the UNSL from Argentina and the Language and Reasoning research group of the UAM Cuajimalpa from Mexico at the PAN’s 2016 Author Profiling task. For the proposed method we adopted a profile-based approach, which has been successfully applied in the Authorship Attribution problem. Thus, we proposed a variation of this tec...

Teaching students disciplinary writing skills is important in supporting them to develop a identity, become member of their scientific communities, and be academically professionally more successful. Disciplinary practices are often implemented at the graduate level where familiarized with processes creating knowledge forms written products within disciplines. However, undergraduate level, inst...

Music is a type of time-series data. As the size data increases, it challenge to build robust music genre classification systems from massive amounts Robust require large labeled data, which necessitates time- and labor-intensive data-labeling efforts expert knowledge. This paper proposes musical instrument digital interface (MIDI) preprocessing method, Pitch Vector (Pitch2vec), deep bidirectio...