Identificação automática de equivalência de conceitos em diferentes idiomas para aprendizado sem fim

• Autor(a) principal: Marino, Silvio Carlos
• Data de Publicação: 2019
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Repositório Institucional da UFSCAR
• Texto Completo: https://repositorio.ufscar.br/handle/ufscar/11661
• topic: Inteligência Artificial; Aprendizado de máquina; Redes neurais; C4.5; XGBoost; Equivalência de conceitos; Artificial Intelligence; Machine learning; Neural networks; Equivalence of concepts; CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO::METODOLOGIA E TECNICAS DA COMPUTACAO

Artificial Intelligence (AI) refers to a machine capable of systematizing and automating tasks that require intelligence when performed by humans. With AI it may be possible to create a decision-making process with an ever-smaller margin of error. In this sense, the project Read the Web and an endless learning computing system called NELL (Never- Ending Language Learning) were created. NELL performs an endless learning process to learn how to read the web better and better. With the success of obtaining knowledge in English, the system was modeled to learn how to extract facts from web pages in other languages, such as Portuguese, French and Spanish. However, the knowledge learned in the different languages is not directly related. Therefore, the main motivation of the research is to develop a mechanism capable of transferring knowledge from one base to another, using machine learning to automatically tell if concepts learned in different languages are the same. The results of the experiments, with the use of neural networks, C4.5 and XGBoost as a model of machine learning, show a significant gain in comparison with the simple use of dictionaries.