Brazil

In this work, we present the platform Boca a Boca Virtual, a kind of virtual catalog that aims to help self-employed professionals and small businesses to start their presence in the digital environment, promoting their services and products in a simple and fast way. The idea emerged during the beginning of the COVID-19 pandemic, especially with social isolation, whose concern, from an economic and social point of view, was to allow autonomous service providers and establishments, in general, to continue offering their products and/or services. Through the platform, a consumer can search for a specific product and service within his own neighborhood and city, strengthening the local economy. In addition, Boca a Boca Virtual is integrated with Google Maps, in such a way that registered developments are also indexed by the Google search engine, improving their visibility and potentially increasing more customers. The platform is fully responsive, combining several recent web development technologies. Today it has more than 140 registered enterprises, from more than 30 Brazilian cities.

WebMedia 2020

Boca a Boca Virtual: Presença Digital para Pequenos Empreendedores

small businesses

electronic commerce

recommendation

The purpose of the AAAI conference series is to promote research in Artificial Intelligence (AI) and foster scientific exchange between researchers, practitioners, scientists, students, and engineers across the entirety of AI and its affiliated disciplines. AAAI-23 is the Thirty-Seventh AAAI Conference on Artificial Intelligence. The theme of this conference is to create collaborative bridges within and beyond AI. Like previous AAAI conferences, AAAI-23 will feature technical paper presentations, special tracks, invited speakers, workshops, tutorials, poster sessions, senior member presentations, competitions, and exhibit programs, and two new activities: a Bridge Program and a Lab Program. Many of these activities are tailored to the theme of bridges and all are selected according to the highest standards, with additional programs for students and young researchers. 
AAAI is providing you with a conference planner, which you can use to help organize your itinerary of activities. This includes talks to attend in person, talks to attend remotely, breaks with colleagues and your site seeing activities. To access this conference planner, please go to [https://aaai-2023.takemobi.io](https://aaai-2023.takemobi.io).

In order to access this site, you need to register. If you haven't already, please register [here](https://aaai.org/Conferences/AAAI-23/registration/).


AAAI 2023

The purpose of the AAAI conference series is to promote research in Artificial Intelligence (AI) and foster scientific exchange between researchers, practitioners, scientists, students, and engineers across the entirety of AI and its affiliated disciplines.

technical paper

Promoted by the Brazilian Computer Society (SBC), the Brazilian Symposium on Multimedia and Web (WebMedia) is the main event of the theme in Brazil and an excellent opportunity for scientific and technical exchange among students, researchers and professionals in the areas of Multimedia, Hypermedia and Web. This year we will be celebrating to 26th edition of WebMedia, which will be held online from november 30th to December 4th .

Webmedia 2020’s programming includes:

– Technical sessions for the presentation of scientific papers
– National and international keynotes
– Panel with companies
– Workshops
– Short Courses
– Open community meetings

The topics of interest for submitting papers are:

– Web and Social Networks
– Multimedia
– Digital TV, Ubiquitous and Mobile Computing

Besides the main track, WebMedia 2020 will have in parallel the Tools and Applications Workshop, works Tools and Applications Workshop, the Workshop on Undergraduate Research Work and the Workshop The Future of Interactive.

The WebMedia 2020 organization is under the responsibility of the Programa de Pós-graduação Doutorado em Ciência da Computação – Associação UFMA/UFPI (DCCMAPI), do Programa de Pós-graduação em Ciência da Computação/ CCET (PPGCC), do Laboratory of Advanced Web Systems/UFMA (LAWS) e do Laboratório de Sistemas Multimídia/UFMA (TELEMÍDIA).).

#PartiuWebMedia2020 #WebMedia2020

Promoted by the Brazilian Computer Society (SBC), the Brazilian Symposium on Multimedia and Web (WebMedia) is the main event of the theme in Brazil and an excellent opportunity for scientific and technical exchange among students, researchers and professionals in the areas of Multimedia, Hypermedia and Web.

This work aims to present the platform on government accountability. named “Cuidando do Meu Bairro” ("Caring for My Neighborhood"), which is a social platform for monitoring and controlling the town´s public spending. The work shows its concept evolution based on stakeholders feedback during the last 8 years that the platform has been contributing to governmental accountability and social participation, The functionalities and software architecture are presented. Also, the main outcomes and social impact that this project provided on civic education, fight against corruption, public transparency and social participation are briefly presented.

Cuidando do Meu Bairro 2.0: Acesso à informação e monitoramento dos gastos da cidade em tempo real

Entering the world of Interactive Digital Television (iDTV) applications can lead to an exhaustive process that involves reading extensive standards and may need a robust middleware solution to run Ginga-NCL applications, which is a subset of Ginga and the standard for interactivity of digital television adopted in Latin America countries. Even though there are some open and commercial solutions for development of Ginga applications available on the market, most of these solutions present downsides such as deep dependency of Ginga engine implementation, need of complex environment setup and they are not very intuitive NCL/NCLua coding platforms. To solve these issues, we created an IDE developed in web technology that makes possible for students and professionals to learn how to develop Ginga-NCL applications. With this tool, developers can write, validate and experiment their applications entirely on the web environment, with no software installation required.

NuGinga Playcode: A web NCL/NCLua authoring tool for Ginga-NCL digital TV applications

The COVID-19 pandemic had substantial impacts on society, both socially and economically, with devastating impacts on our country. Aiming at assisting on coping with such pandemic and providing relevant information for society on matters such as the portion of the population under quarantine, details on philanthropic institutions and the location of health Units, we developed FiscalCovid. Using geoprocessing and crowdsourcing techniques, this system enables the social control as a support tool for the battle against COVID-19.

FiscalCovid: exercendo o controle social na temática da COVID-19

Currently, so-called Recommendation Systems (SRs) have been used to assist users in discovering relevant Points of Interest (POIs) on Location-Based Social Networks (LBSN), such as FourSquare and Yelp. Given the main challenges of data-sparse and geographic influence in this scenario, most of the work on POI recommendations has focused only on improving the effectiveness (i.e. accuracy) of the systems. However, there is a growing consensus that just effectiveness is not sufficient to assess the practical utility of these systems. In real scenarios, categorical and geographic diversities were identified as the main complementary dimensions for assessing user satisfaction and the usefulness of recommendations. The works in the literature are concentrated on only one of these concepts. In this work, we propose a new post-processing strategy, which combines these concepts in order to improve the user’s interest in POIs. Our experimental results in the Yelp data sets show that our strategy can improve user satisfaction, considering different SRs and multiple diversification metrics. Our method is capable of improving diversity by up to 120% without significant losses in terms of effectiveness.

Estratégias para Aprimorar a Diversidade Categórica e Geográfica de Sistemas de Recomendação de POIs

Learning verification is the target of numerous studies that aim to
transform it from its solely classificatory character, in a process of
diagnosing the student's evolution in the learning goals of a
subject. This research proposes a software for monitoring and
authoring evaluative activities, modelled in order to support
teachers and students in the learning verification process. For this,
using the DSR methodology, a bibliographic study was carried out
in the context of school evaluation to support the designing of the
tool. The presented solution was validated through tests and
questionnaires on user experience. The results demonstrated the
potential of the tool to support the school evaluation process.

Avaliar: Sistema para Autoria e acompanhamento de recursos avaliativos

Lack of physical distancing, isolation, and social interactions are
some of the key factors that have contributed to the spread of
COVID-19 and transformed it into this global pandemic. Combining
and correlating human mobility with the COVID-19 cases being
reported may help to determine possible hotspots and provide
guidance on how to possibly make lifestyle changes and choices
so as to avert/limit future waves of this pandemic or a similar one.
This project aims to cope with the research problems involved in
the development of a graphical and interactive tool that performs
intelligent data analysis of visually selected geo-temporal subsets
of collected information. As a result of the project, it was launched
the COVID-19 Borescope, which is shown in Figure 1.

COVID-19 Borescope

In different countries, govern transparency is widely accepted as an effective democratic process. In Brazil, the information-access law contributes to public administration transparency since various public data are available on the Web. However, such data are in different formats and not standardized which makes it difficult to obtain information, mainly in an automated way. Indeed, this work presents an enrichment in an existing open Brazilian judiciary database, a characterization of the available data, and an analysis of the data about judiciary professionals and their earns. The results reveal a lack of linear correlations between the high salaries and their personal benefits. Also, there is a discrepancy between Judiciary salaries and advantages through Brazilian regions, which may be explained by the higher living costs in some regions.

Characterization and Analysis of Open Brazilian Judiciary Data

Context-aware recommendation systems use contextual data to recommend a fully personalized suggestion to their users, for instance, using the massive workloads produced by the usage of mobile apps. In this paper, we collected and analyzed a dataset from social media related to the Belo Horizonte's 2020 Carnival to understand how this event attracts tourists (or Belo Horizonte's non-resident), analyzing their interactions with a large recommendation system. We built a point-of-view of an event mixing its features in two social networks: Twitter and Google Review. Our results show that combining traits lead to better information about the given context using social networks. It helps both the tourists choosing where to travel and the local establishments to provide better services.

Analyzing A Touristic Event Popularity Using Social Networks

Wikipedia, with more than 50 billion pages, is one of the most popular free online encyclopedias in the world. It is based on user-generated content, in other words, anyone with internet access can write and make changes to its articles, hence the information quality of the encyclopedias is often criticized. Therefore, assigning the correct class of quality to Wikipedia articles is crucial for the experience of both authors and readers when using this large repository of information. In this paper, we present an approach relying on deep neural networks for quality classification of Wikipedia articles. The experiments consisted of testing three different models to achieve the best possible result: the first one using a model without multiview, the second using multiview with three views and the third one using multiview with six views. Finally, we compared our results with a model that used Support Vector Regression as the learning algorithm, achieving similar values with our multiview models.

Automatic Content Quality Estimation Using Deep Neural Networks in Collaborative Encyclopedias on the Web

The spread of misinformation, hate speech, or sexist discourse had become a significant problem, especially on chat platforms. This article describes a data collection and processing tool to support research on users’ behavior exposed to these contents. Our motivation is the recent need to study profiles that propagate this type of information and the need to understand these new dissemination mechanisms. This tool provides a web configuration panel and a mobile application for data collection. Using a chatbot mechanism, the panel allows researchers to perform personalized experiments to analyze specific issues. The application collects the user’s basic profile, allows interaction with the chatbots sent by the researcher, and runs on the volunteers’ devices, similar to a real messaging application such as WhatsApp or Telegram. The data generated regarding the user’s interactions with the application can be exported for analysis through the panel. Also, we describe the insertion of optional codes that can be executed in parallel to the conversations, helping in sophisticated personalizations. We believe that the proposed open-source tool will help researchers from different areas, even without computer programming skills, to understand fundamental mechanisms of user behavior in mobile chat systems.

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