Emerson Cabrera Paraiso

Verified

Emerson verified their affiliation via an institutional email.

Learn more

Verified

Emerson verified their affiliation via an institutional email.

Learn more

• PhD - Associate Professor at PPGIa - PUCPR - Brazil
• Professor (Full) at Pontifical Catholic University of Paraná

Objetivos: A desidentificação de narrativas clínicas é essencial para proteger a privacidade dos pacientes e garantir a conformidade com as regulamentações. No entanto, é uma tarefa complexa devido aos distintos tipos de entidades a serem desidentificadas e à necessidade de processar os textos localmente, por questões de segurança e privacidade. Mé...

Purpose-The study aims to investigate the most popular content discussed by social media influencers on YouTube and its associated valence, to delineate the content categories favored by top Brazilian influencers, and to assess their impact on consumer digital engagement. Theoretical framework-This study draws upon influencer marketing, social medi...

In multi-label classification, data can have multiple labels simultaneously. Two approaches to this issue are either transforming the multi-label data or adapting single-label algorithms for multi-label data. Despite the problem transformation’s effectiveness, some algorithms use fixed parameters to determine the number of subproblems, and the labe...

As social media influencers have become a global phenomenon, brands are channeling substantial resources into influencer marketing campaigns. Researchers are keenly exploring diverse content factors that wield influence in online social spheres, including linguistic elements. However, uncertainties persist regarding their association with digital c...

The electronic health record (EHR) data, widely used by hospitals and healthcare professionals, contain valuable information about the patient and treatments and has become increasingly relevant to clinical natural language processing (NLP) tasks. Although the growing number of EHR systems, these medical data contain sensitive information and canno...

Electronic Health Records are a valuable source of information to be extracted by means of natural language processing (NLP) tasks, such as morphosyntactic word tagging. Although there have been significant advances in health NLP, such as the Transformer architecture, languages such as Portuguese are still underrepresented. This paper presents tagg...

Unstructured data in electronic health records, represented by clinical texts, are a vast source of healthcare information because they describe a patient's journey, including clinical findings, procedures, and information about the continuity of care. The publication of several studies on temporal relation extraction from clinical texts during the...

Question answering (QA) systems aim to answer human questions made in natural language. This type of functionality can be very useful in the most diverse application domains, such as the biomedical and clinical. Considering the clinical context, where we have a growing volume of information stored in electronic health records, answering questions a...

Information Extraction techniques can retrieve useful information from unstructured data that improve data analytics’ effectiveness and play a key role in the consumer decision-making process. The growth of sponsored content videos on social media increases the demand on knowing the effectiveness of the sponsored investment in the engagement result...

Churn can be interpreted as customer defection and can be considered one of the most critical challenges in the Game Analytics domain because of its impact on the game industry's profit. When predicting churn, the first step is defining what is considered churn, which can change depending on the players' behaviors and approaches. This work studied...

Churn can be interpreted as customer defection and can be considered one of the most critical challenges in the Game Analytics domain because of its impact on the game industry's profit. When predicting churn, the first step is defining what is considered churn, which can change depending on the players' behaviors and approaches. This work studied...

A significant part of Natural Language Processing (NLP) techniques for sentiment analysis is based on supervised methods, which are affected by the quality of data. Therefore, sentiment analysis needs to be prepared for data quality issues, such as imbalance and lack of labeled data. Data augmentation methods, widely adopted in image classification...

This study introduces the system submitted to the eHealth-KD Challenge 2021 by the PUCRJ-PUCPR-UFMG team. We proposed a multilingual BERT-based system for joint entity recognition and relation extraction in multidomain texts. Our end-to-end multitasking model benefits from the transformer architecture, which has proved to capture better the global...

Epidemiologists constantly search for methodologies that help them better understand how diseases work. Populations urge these improvements to combat these diseases more effectively. The literature presents several authors defending the idea that epidemiologists should be able to develop causal models. In this area, the technique of structural equa...

Popularity on YouTube is an important metric for influencers and brands. It is linked to video relevance, content, and features that attract audience attention and interest. We present and test a model of YouTube video popularity drivers that trigger several engagement actions (i.e., number of views, likes, dislikes, and comments). These drivers in...

Objectives: Clinical Named Entity Recognition is a critical Natural Language Processing task, as it could support biomedical research and healthcare systems. While most extracted clinical entities are based on single-label concepts, it is very common in the clinical domain entities with more than one semantic category simultaneously. This work prop...

Objetivo: A pandemia causada pelo novo coronavírus (SARS-CoV-2) caracteriza-se como o maior desafio do século 21. Neste contexto, procurou-se levantar um panorama geral de dados de usuários do Twitter, no Brasil, relacionados à COVID-19. Métodos: Utilizando de técnicas de Processamento de Linguagem Natural, foi aplicado um modelo Word2Vec CBOW em u...

With the growing number of electronic health record data, clinical NLP tasks have become increasingly relevant to unlock valuable information from unstructured clinical text. Although the performance of downstream NLP tasks, such as named-entity recognition (NER), in English corpus has recently improved by contextualised language models, less resea...

With the growing number of electronic health record data, clinical NLP tasks have become increasingly relevant in healthcare, unlocking valuable information from unstructured clinical text. Although the performance of downstream tasks, such as named-entity recognition (NER), in English corpus have recently improved by contextualised language models...

In this work, the technical feasibility of working with audio transcriptions from Youtube is analyzed, as well as presenting a method that allows data acquisition, pre-processing, and post-processing to work with this type of data. A topic modeling approach with the latent dirichlet allocation algorithm is used. An approach is also presented to dyn...

Objective To develop, validate and adapt a protocol for a self-management app targeting adolescents with type 1 diabetes. Methods Methodological study conducted from February 2017 to March 2019 in three stages: development; content validation; and adaptation. In stage 1, the main issues about self-management practices in type 1 diabetes were discu...

During the development cycle of a project, it is common for software requirements and functionality to change and for code errors to occur. To deal with these unforeseen changes, the artifact known as change request, which is a formal proposal to alter a system, is used. Its assignment is an important step in the development process. Projects can r...

In this article, we present and test a model of drivers for video post popularity on YouTube. In this conceptual model, video characteristics such as linguistics style, subjectivity, emotion polarity and video category influence online video popularity on YouTube (i.e. the number of likes, dislikes, and comments). The results of the analysis of mor...

Players can change their interest in continuing playing due to many reasons, such as the game content available to them. Therefore, game upgrades play an important role as they have the potential to influence players, being it a “double-edged sword”, as players may like the new challenges or not. Among the active players, “whales” are those players...

The increasing use of social networks has made opinion mining an important field in the area of Natural Language Processing. The analysis of texts from the reader perspective tends to generate multi-label data since one can interpret the text using different contexts. In this paper , a new method for multi-label classification is proposed to identi...

Organizations have been increasingly relying on software development to manage their business, making it an essential activity. Companies have been using collaborative development environments to speed up their deliveries, resulting in projects tending to be produced by developers from different parts of the world with different cultures. In this c...

Dialogue systems intend to facilitate the interaction between humans and computers. A key element in a dialogue system is the conceptual model which represents a domain. Folksonomies are very simple forms of knowledge representation which may be used to specify the conceptual model. However , folksonomies by nature have ambiguity. In this paper, we...

Despite the great number of Systems of Systems (SoS) being developed, building them still remains hard and difficult. Currently, there is a lack of methods capable of supporting architects for building an actual SoS. In this paper we introduce an original method called GAMBAD for developing an SoS from a practical point of view. Our method guides t...

The increase in the number of Internet users and the strong interaction brought by Web 2.0 made the Opinion Mining an important task in the area of natural language processing. Although several methods are capable of performing this task, few use multi-label classification, where there is a group of true labels for each example. This type of classi...

Sentiment Analysis is an emerging research field traditionally applied to classify opinions, sentiments and emotions towards polarity and subjectivity expressed in text. An important characteristic to automatic emotion analysis is the standpoint, in which we can look at an opinion from two perspectives, the opinion holder (author) who express an op...

In this paper, we present a Machine Learning approach based on commitment to deal with two risky situations over game usage lifecycle: the prediction of churn and players remaining lifetime. These risky situations are gauged by game producers to try to maintain the players motivated, intervening when players tend to leave. The problem is that this...

Although the concept of System of Systems (SoS) has become quite popular, most applications are still hand crafted. In this paper we present a framework, called MBA for Memory-Broker-Agent, addressing the development of systems of systems from an engineering perspective. The main features of the framework result from the experience gained from buil...

In this paper, we present a Machine Learning based approach to identify the Niche stage in Massively Multiplayer Online Role-Playing Games during their usage lifecycle. The Niche stage is the last stage of the lifecycle and represents a risky situation, because its rentable us-age may end soon, as the engagement of the new players are dropping. Thi...

A system of systems (SoS) represents a set of independent systems cooperating to achieve a common goal. Developing an SoS is complex and difficult, requiring significant efforts from system architects to coherently interface systems and make them interoperable. In this research, a core architecture to simplify the development of SoS supporting coll...

The digital game product lifecycle is a model that shows the usage of a game over time, being also called usage lifecycle. This lifecycle includes aspects related to motivational usage, modeling and tendencies of future behavior, providing the opportunity to apply advanced techniques of artificial intelligence to deal with those aspects. The main g...

Este trabalho apresenta uma pesquisa em andamento sobre categorias gramaticais que podem ser exploradas como indicadores de emoção em textos escritos. Diferentemente de pesquisas sobre análise de sentimentos que se concentram em itens lexicais, este estudo baseia-se na gramática sistêmico-funcional [Halliday e Matthiessen 2014] a fim de mapear padr...

Objetivo: Examinar os recursos de aplicativos para dispositivos móveis destinados ao autocuidado de adolescentes com diabetes mellitus tipo 1. Métodos: Revisão integrativa por meio da busca de artigos nos periódicos indexados nas bases de dados: Cumulative Index to Nursing and Allied Health Literature, Cochrane Library, Literatura Latino-Americana...

Among the different types of digital games, Massively Multiplayer Online Role-Playing Games (MMORPGs) are one of the most popular. Game producers use usage data to compute metrics to analyze their game lifecycles. The most popular is the MAU (Monthly Active Users), which indicates the number of active players in each timestamp. MAU only describes h...

ADHD is the most commonly diagnosed psychiatric disorder in children and, although its diagnosis is done in a subjective way, it can be characterized by abnormality work of specific brain regions. Datasets obtained by rs-fMRI cooperate to the large amount of brain information, but they lead to the curse-of-dimensionality problem. This paper aims to...

Good Decision Support Systems require three main features: (i) a good handling of the domain data and information; (ii) an efficient user interface; and (iii) a good knowledge of past decisions. Usually such features are handled by different specialized systems difficult to integrate. In this research we keep specialized systems independent, focusi...

O TDAH é a disfunção psiquiátrica mais diagnosticada em crianças e o estudo de regiões cerebrais com comportamentos anormais em neuroimagens tem ganhado atenção. O principal problema em análises de neuroimagens é a chamada maldição da dimensionalidade, e um dos responsáveis por isso são as matrizes de conectividade obtidas pelo rs-fMRI. Este trabal...

Sentiment Analysis has become a critical research area in recent days and pervasive in real life. Considering the identification of Emotions from textual content, we propose the Hourglass of Emotions as the feature that comes from the intensity of affective dimensions and combination thereof. Thus, based on a news dataset labeled with six primary E...

Massively Multiplayer Online Role-Playing Games can be divided in different stages according to their maturity in the usage lifecycle, such as: introduction, growth, maturity, decline and niche. In this paper we present a game independent method to predict the niche stage using a new measure called Commitment. Since it is the last stage, the game p...

Sentiment Analysis has become a critical research area in recent days and pervasive in real life. Considering the identification of Emotions from textual content, we propose the Hourglass of Emotions as the feature that comes from the intensity of affective dimensions and combination thereof. Thus, based on a news dataset labeled with six primary E...

Applications based on Opinion Mining and Sentiment Analysis are critical tools for information-gathering to find out what people are thinking. It is one of the most active research areas in Natural Language Processing, and a diversity of strategies and approaches have been published. We evaluate two strategies-Cognitive-based Polarity Identificatio...

Noctua is a web tool to assist in Knowledge Acquisition and Collaborative Knowledge Construction processes. Noctua has an innovation: a Virtual Catalyst designed to facilitate the task of eliciting and validating knowledge. The Virtual Catalyst queries participants, proposing new knowledge, seeking confirmation to the knowledge already elicited, an...

Este artigo relata o processo de construção e anotação de um corpus de notícias para a Análise de Sentimento. Os textos, extraídos de jornais do Brasil, foram anotados com as emoções básicas (alegria, tristeza, raiva, surpresa, repugnância e medo) ou a ausência de emoção (neutro). O processo de anotação resultou em valor de concordância baixo (kapp...

The SVM classifier has been used in many methods to identify emotions in text due to their good generalization capability and robustness with high dimensionality data. However, most textual corpora usually subject to such methods are naturally imbalanced. As a consequence, the SVM, sensitive to imbalance data, assigns to most texts the majority cla...

Software development is a collaborative activity, dependent on technology and performed by groups of people. The software technology involved is an important factor, since it provides the necessary tools for the development of the work. This paper presents a collaborative virtual workspace that follows the code development, comparing it with the mo...

Knowledge discovery is the process of discovering useful knowledge in a broad range of sources, such as relational databases, images, or texts. Dialogues are generated by interaction between people using natural language and can be used as a source of information. Once discovered, knowledge needs to be represented, and there are several approaches...

A dialogue system allows a human to interact with a computer, through the natural language. One of the main components of a dialogue system is the Conceptual Model. The Conceptual Model represents a domain and its specification is given by several forms of knowledge representation. We propose to represent it using folksonomies. We describe a method...

The automatic identification of emotions in texts has shown significant results in diverse applications. The SVM (Support Vector Machine) classifiers have been used in many methods to identify emotions in text due to their good generalization capability and robustness with high dimensionality data. However, most textual corpora usually subject to s...

Document source code is seen as a boring time consuming task by several developers. However, a welldocumented source code, allow developers to have a better visibility into what was and is being developed, helping, for example, the reuse of the code. This study presents a semi-automatic method for documentation of source code from the existing arti...

This paper presents the FOLKUS-SD a module of CSCW-SD, intend to build Folksonomies from source codes. The CSCW-SD is an architecture to integrate tools in a development environment through a Multi-Agent System. The Folksonomies are built using dynamic data collected during codification. The Folksonomies' entities are represented by the module as:...

Resumo. A identificação automática de emoções em textos tem apresentado resultados significativos em diversas aplicações. Neste artigo, é apresenta-da uma abordagem utilizando Máquinas de Vetores de Suporte para identi-ficar emoções em textos escritos em Português do Brasil. O corpus utilizado no experimento é composto de notícias extraídas de um j...

Este artigo apresenta um método de pré-processamento de dados textuais que pode ser utilizado em um processo de identificação automática de emoções em textos para o Português Brasileiro.

Collaboration is an important issue when developing software, because it involves working together towards a common goal. This work presents OPERAM, a collaborative semantic workspace that allows comparing the modeling performed at earlier stages of software development with JAVA code. OPERAM provides useful information for professionals involved i...

This paper presents a method for moral harassment identification inelectronic messages (e-mail) written in Brazilian Portuguese. The method isalso capable of identifying the emotions associated with each message. Themoral harassment is briefly presented, with its concepts and main elements.Our method to moral harassment identification in electronic...

The lack of tools for small software development teams leads us to propose an architecture to better support it. The multi-agent system (MAS) based architecture is called CSCW-SD. CSCW-SD has a module (MODUS-SD) that models users for better system customization and usability. In this paper, we present an enhancement to this module to help dynamical...

The Abstract Computational Model of Awareness for Community Identification (AMACI) is based on the contents of resources created or used by users, which allows noticing others that perform or have performed activities in similar contexts, thereby identifying potential communities and teams. The model was evaluated through experiments using data fro...

We have been researching in CSCW for small teams for the last years. As we presented in previous works, small software development teams have special needs and requirements that must be taken into account when designing tools for supporting cooperation of their participants. We have already proposed the architecture of a system (called CSCW-SD) to...

As abordagens existentes na literatura não são modeladas para detecção do aliciamento sexual de menores, mas apenas fazem a descoberta do estágio de aliciamento numa comunicação entre o agressor e sua vítima. Além disto, mostram baixa eficiência em função do emprego de um perfil único para a descoberta dos estágios. Este artigo considera a descober...

The automatic detection of emotions in texts has presented significant results in several and different situations. In this paper, we present an approach to identify automatically emotions in short texts written in Brazilian Portuguese. Each text is processed using an algorithm based on the Latent Semantic Analysis theory. Experimentations have sho...

During the software development cycle, artifacts (source-code, documentation, user manuals, etc.) are written, most of them, cooperatively. Each participant in a software development team plays a specific role, but may write an artifact cooperatively with participants playing different roles. In large and distributed teams the roles are well-define...

Visual Interactive Environments, such as Alice, has been used as an alternative in computer programming learning. Based on this idea, this work applied the Alice environment in course of computer programming for students starting their undergraduate course. Results show that, unlike previous works, the Alice did not contribute to raise the rate of...

This paper presents Noctua, a tool to assist in Knowledge Acquisition and Collaborative Knowledge Construction processes. Noctua contains an innovation: a virtual catalyst designed to facilitate the task of eliciting and validating knowledge. The virtual catalyst queries collaborators, proposing new knowledge, seeking confirmation to the knowledge...

Software developers often face the task of documenting source code. For many of them, documenting code development is a boring task. However, source code documentation is an important task, especially when dealing with groups of developers. An updated documentation allows group members to have greater visibility on what has been and is being develo...

Divergences in conceptual modeling choices are inherent to the collaborative ontology development. Such divergences have been typically solved through some process of negotiation among the participants of the development process. When negotiating, the participants argue to defend their ideas based on their past experiences. We propose to support an...

Building application domain models is a time-consuming activity in software engineering. In small teams, it is an activity that involves almost all participants, including developers and domain experts. In our approach, we support the knowledge engineering activity by reusing tagging done by team participants when they search information on the Web...

Noctua is a tool to assist the Knowledge Acquisition and Collaborative Knowledge Construction processes. Noctua contains a virtual catalyst designed to facilitate the task of eliciting and validating knowledge. The virtual catalyst queries collaborators, proposing new knowledge, seeking confirmation to the knowledge already elicited, and showing co...

In this paper, we discuss the construction of dialogs for Personal Assistant Agents that are in charge of the interface between users and a Multi-Agent System. Such a system aims at providing support for small teams developing software collaboratively. Small teams have specific needs such as the integration of free or open-source tools or the suppo...

Intelligent agent-based assistants are systems that try to simplify peoples work based on computers. Recent research on intelligent assistance has presented significant results in several and different situations. Building such a system is a difficult task that requires expertise in numerous artificial intelligence and engineering disciplines. A ke...

The necessity of lowering the execution of system tests' cost is a consensual point in the software development community. The present study presents an optimization of the regression tests' activity, by adapting a test cases prioritization technique called Failure Pursuit Sampling-previously used and validated for the prioritization of tests in ge...

In this paper, we discuss the construction of dialogs for Personal Assistant Agents that are in charge of the interface between users and a Multi-Agent System. Such a system aims at providing support for small teams developing software collaboratively. These small teams have specific needs such as the integration of free or open-source tools or the...

OBJETIVO: Identificar, com o auxílio de técnicas computacionais, regras referentes às condições do ambiente físico para a classificação de microáreas de risco. MÉTODOS: Pesquisa exploratória, desenvolvida na cidade de Curitiba, PR, em 2007, dividida em três etapas: identificação de atributos para classificar uma microárea; construção de uma base de...

To identify, with the assistance of computational techniques, rules concerning the conditions of the physical environment for the classification of risk micro-areas. Exploratory research carried out in Curitiba, Southern Brazil, in 2007. It was divided into three phases: the identification of attributes to classify a micro-area; the construction of...

The research on CSCW and groupware systems focus the activities of distributed teams involved in large projects by means of tools for communication and awareness. The activities of small collocated teams are often neglected. Analyzing preliminary requirements of small teams, it is possible to observe the need of tools to help the elaboration of pro...

We have been using personal assistants (PA) coupled with multi-agent systems (MASs) in several CSCW applications. Since we are considering professional environments, where users have many tasks to perform, and where users are using several different applications at the same time (browsers, CADs, etc.), the PA interface should motivate users to keep...

Most CSCW and groupware systems focus the activities of distributed teams involved in large projects by means of tools for communication and awareness. The activities of small collocated teams are often neglected. Analyzing preliminary requirements of small teams, it is possible to observe the need of tools to help the elaboration of project docume...

The arrhythmias or abnormal rhythms of the heart are common cardiac riots and may cause serious risks to the life of people, being one of the main causes on deaths. These deaths could be avoided if a previous monitoring of these arrhythmias were carried out, using the Electrocardiogram (ECG) exam. The continuous monitoring and the automatic detecti...

WebAnima is an interface agent specially designed to assist team members of a CSCW application during their daily work based on computers. In WebAnima, the intelligent behavior is guaranteed thanks to a conversational interface and ontologies that support semantic interpretation. We believe that embodied conversational assistants will improve the q...

In this paper, we present an ontology-based utterance interpretation mechanism for intelligent conversational interfaces. We describe how this mechanism was embedded in a conversational interface applied to personal assistant agents. The main goal of such approach is to offer a system capable of performing tasks through an intuitive interface, allo...