Angelo Loula

Felipe José D. Sousa, Sarah P. Cerqueira, João Queiroz et al.

The computational generation of poems is a complex task, which involves several sound, prosodic and rhythmic resources. In this work we present PROPOE 2, with the extension of structural and rhythmic possibilities compared to the original system, generating poems from metered sentences extracted from the prose of Brazilian literature, with multiple rhythmic assembly criteria. These advances allow for a more coherent exploration of rhythms and sound effects for the poem. Results of poems generated by the system are demonstrated, with variations in parameters to exemplify generation and evaluation using various criteria. A geração computacional de poemas é uma tarefa complexa, que envolve diversos recursos sonoros, prosódicos e rítmicos. Neste trabalho apresentamos PROPOE 2, com a ampliação de possibilidades estruturais e rítmicas em relação ao sistema original, gerando poemas a partir de sentenças metrificadas extraídas da prosa da literatura brasileira, com múltiplos critérios rítmicos de montagem. Esses avanços permitem uma exploração mais coerente de ritmos e efeitos sonoros para o poema. Resultados de poemas gerados pelo sistema são demonstrados, com variações de parâmetros para exemplificar a geração e a avaliação pelos variados critérios.

Rafael Glauber, Angelo Loula

Recommendation Systems (SR) suggest items exploring user preferences, helping them with the information overload problem. Two approaches to SR have received more prominence, Collaborative Filtering, and Content-Based Filtering. Moreover, even though studies are indicating their advantages and disadvantages, few results empirically prove their characteristics, similarities, and differences. In this work, an experimental methodology is proposed to perform comparisons between recommendation algorithms for different approaches going beyond the "precision of the predictions". For the experiments, three algorithms of recommendation were tested: a baseline for Collaborative Filtration and two algorithms for Content-based Filtering that were developed for this evaluation. The experiments demonstrate the behavior of these systems in different data sets, its main characteristics and especially the complementary aspect of the two main approaches.