Rede Social Gamer com modelagem do algoritmo K-means para indicação de novas amizades

• Autor(a) principal: Ribeiro, Marcus Antonio Rufino
• Data de Publicação: 2022
• Tipo de documento: Trabalho de conclusão de curso
• Idioma: por
• Título da fonte: Repositório Institucional da UFU
• Texto Completo: https://repositorio.ufu.br/handle/123456789/36551
• topic: Rede social; Indicação de amizades; K-means; Método Elbow; CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO::METODOLOGIA E TECNICAS DA COMPUTACAO::SISTEMAS DE INFORMACAO

Social networks for the Games domain on the Internet are already a consolidated reality. Thanks to practicality, to mobile access always at hand, and to the fact that we can play anywhere, mobile games are dominating this sector. However, a survey has shown that players have difficulty finding other geographically close players who enjoy this type of sport to connect with. Thus, this work aims to create a social network focused on the gamer audience. For its development, programming languages such as HTML, CSS, Java Script, PHP, and database technologies were used. For the friendship recommendation, the k-means clustering method was used in conjunction with the Elbow Method to find out what would be the ideal value of K for the application. Experiments carried out with synthetic data showed the viability of the proposal.