Sistema de recomendação de restaurantes, baseado em três tipos diferentes de filtragem de dados, nos bairros do Recife-PE

Abstract

Considering that the city of Recife is in third place for gastronomic centers in Brazil, and that currently the amount of information present on the internet is bordering on infinity, tourists and even the local population go to the most popular restaurants. A consequence of this is that small accessories, which do not have a strong publicity for their brand, end up going out of business in the first five years of existence. Therefore, a research was carried out on recommendation systems, an analysis purpose for the development of a restaurant recommendation system, based on three different types of data filtering techniques, in the neighborhoods of the city of Recife. Therefore, it is necessary to explain the fundamentals of the filtering techniques that will be used in the development of the system, in addition to identifying how to define, collect, treat and analyze the data provided for the construction of the system, analyze the development of a recommendation-based system in the content, analyze the development of a recommendation system, based on the user, analyze the development of a hybrid recommendation system and finally identify which recommendation technique best results. A study is then carried out on the database, selection, collection and processing of data provided for the construction of the system, in addition to modeling a sample of people and results to be recommended, a study was also carried out on recommendation systems, definition, emergence and main filtering techniques, used in similar works, thus it was necessary to define which attributes and parameters to be collected, in addition to a modeling of the data capture form and development of the three selected collaborative filtering techniques, and finally, system tests are carried out to prove its functioning and analysis of collected data. Therefore, it appears that although the content-based filtering technique stands out in the results, the difference between this type of filtering and collaborative filtering was not significant, which imposes the observation that the recommendation system, based on neighborhoods , brings ease and convenience to users, in addition to promoting the brand of neighborhood restaurants and expanding tourism in the city of Recife, but it requires more interaction and information from registered users, to become more precise in their recommendations.