TCC - Bacharelado em Ciência da Computação (Sede)
URI permanente para esta coleçãohttps://arandu.ufrpe.br/handle/123456789/415
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Item Coh-Metrix PT-BR: uma API web de análise textual para à educação(2021-03-02) Salhab, Raissa Camelo; Mello, Rafael Ferreira Leite de; http://lattes.cnpq.br/6190254569597745; http://lattes.cnpq.br/6761163457130594CohMetrix is a computational system that provides different measures of textual analysis, including legibility, coherence and textual cohesion. These measures allow a more indepth analysis of different types of educational texts such as essays, answers to open questions and messages in educational forums. This paper describes the features of a prototype, which encompass a website and an API, of a Brazilian Portuguese version of CohMetrix measures.Item Inferência automática de nível de dificuldade de receitas culinárias usando técnicas de processamento de linguagem natural(2020-12-21) Britto, Larissa Feliciana da Silva; Pacífico, Luciano Demétrio Santos; Ludermir, Teresa Bernarda; http://lattes.cnpq.br/6321179168854922; http://lattes.cnpq.br/9521600706234665; http://lattes.cnpq.br/5058497100007411In this work, a tool for inferring the degree of difficulty of cooking recipes will be proposed. The inference will be made by the textual classification of the recipe preparation methods. The tool will be a fundamental piece to the development of a contextaware contentbased cooking recipe recommendation system. Some of the main classifiers in Text Classification literature will be adopted, in addition to different feature extraction methods. An experimental evaluation is performed, in order to select the best approaches to compose the system.Item Recomendação e geração de receitas baseada na substituição de ingredientes(2020-12-21) Oliveira, Emília Galdino de; Pacífico, Luciano Demétrio Santos; Ludermir, Teresa Bernarda; http://lattes.cnpq.br/6321179168854922; http://lattes.cnpq.br/9521600706234665; http://lattes.cnpq.br/6278486720525640Nowadays, even with the increasing number of recipe sharing websites and systems, users may have difficulty to search specific dishes through the massive amount of data contained in such repositories. Also, finding recipes which best fit a handy set of ingredients, while at the same time contemplate some user wishes and restrictions, may become a very time consuming or even impossible task. In this work, we propose a new recipe recommendation and generation system, based on the substitution of recipe ingredients and a datadriven approach, in an attempt to help users finding a recipe that contemplates both their desires and food restrictions, avoiding food wastes.