TCC - Bacharelado em Ciência da Computação (Sede)
URI permanente para esta coleçãohttps://arandu.ufrpe.br/handle/123456789/415
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Item Análise de um sistema de recomendação de restaurantes sensível ao contexto sobre o grau de satisfação dos usuários(2023-09-01) Melo Filho, Carlos Olimpio Rodrigues de; Silva, Douglas Véras e; http://lattes.cnpq.br/2969243668455081; http://lattes.cnpq.br/6986499479035317Popular applications of recommender systems can be found in many areas. In the food business, platforms such as TripAdvisor stand out for suggesting specialized restaurant recommendations based on various types of relevant information, such as reviews from other users for the menu, atmosphere and recommendations for the closest restaurants are some of the specialties of these platforms. With the possibility of using new data sensitive to the user’s context, the main objective of this work is to evaluate the usage of the reason of going to the restaurant to reorganize the final restaurants recommendation through a context-based post-filtering. To achieve the goal, a mobile application was developed, the SR Recife Restaurants, to assess the degree of satisfaction of real users to the recommended restaurants, an online evaluation approach, using questionnaires, was used. When carrying out the experiment with 15 users, it was possible to notice an increase of 26.67% in the degree of satisfaction of the top-5 first recommendations when using the trip type to the restaurant as context data for the post-filtering phase.Item Detecção de aplicativos maliciosos no sistema operacional android por meio de análise estática automatizada(2017-09-06) Silva, Diógenes José Carvalho da; Lins, Fernando Antonio Aires; http://lattes.cnpq.br/2475965771605110; http://lattes.cnpq.br/0986435158192139The mobile applications platform known as Android provides a wide an open environment of application development to all kinds of software, however this freedom can bring possible software security vulnerabilities that can be used unfortunately to create threats to the operation system. There are vulnerabilities that comes from software and hardware that allows the creation of threats called: spyware, diverse kinds of malware, and with raising popularity, the ransomware. In this case is necessary to build application analysis to find out threats that are increasing in size and complexity. To accomplish this task, this research proposes a technique that combines multiple strategies to orchestrate a new technique that can detect threats and vulnerabilities inside applications developed to the Android mobile operational system. The strategy combines automatic static analysis and threat profile identification by metadata from an external source. Using techniques like web crawling to collect metadata from application stores, we generated a data set with 1000 applications, which 500 are infected and 500 aren't, using balancing technique such as super sampling, extraction and selection of features like: TF-IDF, frequency of terms, feature conversion from nominal to binary and normalization. Using the generated data set to create classification models with the most used machine learning algorithms used by other researchers, we could provide precision metrics, false positives, and false negatives at acceptable rates, comparable to other researches that presents the same performance metrics.Item Lamparina: solução para auxiliar mulheres rurais em situação de violência(2021-12-09) Ferreira, Ariany da Silva; Sampaio, Suzana Cândido de Barros; http://lattes.cnpq.br/0066131495297081; http://lattes.cnpq.br/4697861062895175In recent decades, even with several government attempts to reduce violence against women, the statistics continue to grow. What is considered a serious violation of human rights is still a reality for many women around the world. In geographically isolated or inaccessible regions, women in addition to becoming more vulnerable to violence, become invisible in the face of statistics and public policies to combat violence against women. Using exploratory research to deepening what has been done to reduce violence against women, understand the concept of social innovation, mobile development and the creation of a minimum viable product, the Lamparina application aims to help rural women in the Pajeú hinterland in a situation of violence.Item Smart Tour PE: um aplicativo android para monitoramento remoto de pontos turísticos no estado Pernambuco(2021-07-13) Fonsêca, Eder Lucena Andrade da; Araújo, Danilo Ricardo Barbosa de; http://lattes.cnpq.br/2708354422178489; http://lattes.cnpq.br/9564226085565142The tourism sector has been growing sustainably since the 90s, and not even the period of economic downturn at the time was able to stop it. In recent years, around 2018 and 2019, the sector was breaking new records of international arrivals, with the COVID19 pandemic being the only “disaster” capable of stopping this success streak. More than a year after the beginning of the pandemic, thanks to the medical advances allowing the creation of effective vaccines and viable means to return to normality, it is expected that the search for tourist destinations will grow again very soon, with ecotourism being pointed out as the most likely niche to be sought after. Therefore, it is important that technological solutions are made available to support tourism, especially ecotourism. This undergraduate thesis is the idealization of a tool to help tourists dynamically choose their next travel destination based on the location’s real time weather. Accurate information about the climate will ensure that tourists make the most of their leisure time, being able to visit a place that most suits them, from beaches to tree lined hiking trails in preservation areas, based on climate reports. The real time weather reports from tourist attractions will be displayed through an application idealized in this undergraduate thesis, designed to work on mobile devices with internet access. This application will use information from weather stations installed in tourist attractions in the state of Pernambuco during the execution of the research project related to this undergraduate thesis, also offering the user geolocation data, video streaming from local cameras, routes to access the desired location, as well as additional information about utility telephones and a panic buttons for emergencies. According to usability tests carried out with the target audience, only 3% of them considered the application difficult to use and 97% considered it easy or extremely easy to use. In addition, the application scored 75 points in the Net Promoter Score indicator, with the average for the tourism sector in Brazil being 70 points, additionally to several other positive indicators to be explained later.