scholarly journals Porttinari - a Large Multi-genre Treebank for Brazilian Portuguese

2021 ◽  
Author(s):  
Thiago Alexandre Salgueiro Pardo ◽  
Magali Sanches Duran ◽  
Lucelene Lopes ◽  
Ariani Di Felippo ◽  
Norton Trevisan Roman ◽  
...  
Keyword(s):  
State Of The Art ◽  
Brazilian Portuguese ◽  
Relevant Research ◽  
International Model ◽  
Research Questions

This paper presents the project of a large multi-genre treebank for Brazilian Portuguese, called Porttinari. We address relevant research questions in its construction and annotation, reporting the work already done. The treebank is affiliated with the “Universal Dependencies” international model, widely adopted in the area, and must be the basis for the development of state of the art tagging and parsing systems for Portuguese, as well as for conducting linguistic studies on morphosyntax and syntax for this language.

A Legitimacy Crisis of Representative Democracy?

2017 ◽  
Author(s):  
Jacques Thomassen ◽  
Carolien van Ham
Keyword(s):  
Empirical Evidence ◽  
State Of The Art ◽  
Short Description ◽  
The State ◽  
Political Support ◽  
Systematic Fashion ◽  
Research Questions ◽  
The 1960S ◽  
Established Democracies ◽  
Legitimacy Crisis

This chapter presents the research questions and outline of the book, providing a brief review of the state of the art of legitimacy research in established democracies, and discusses the recurring theme of crisis throughout this literature since the 1960s. It includes a discussion of the conceptualization and measurement of legitimacy, seeking to relate legitimacy to political support, and reflecting on how to evaluate empirical indicators: what symptoms indicate crisis? This chapter further explains the structure of the three main parts of the book. Part I evaluates in a systematic fashion the empirical evidence for legitimacy decline in established democracies; Part II reappraises the validity of theories of legitimacy decline; and Part II investigates what (new) explanations can account for differences in legitimacy between established democracies. The chapter concludes with a short description of the chapters included in the volume.

scholarly journals Users roles identification on online crowdsourced Q&A platforms and encyclopedias: a survey

2021 ◽  
Author(s):  
Akrati Saxena ◽  
Harita Reddy
Keyword(s):  
Network Analysis ◽  
Knowledge Sharing ◽  
Informal Learning ◽  
Social Roles ◽  
Online Discussion ◽  
State Of The Art ◽  
Temporal Analysis ◽  
The State ◽  
Open Research ◽  
Research Questions

AbstractOnline informal learning and knowledge-sharing platforms, such as Stack Exchange, Reddit, and Wikipedia have been a great source of learning. Millions of people access these websites to ask questions, answer the questions, view answers, or check facts. However, one interesting question that has always attracted the researchers is if all the users share equally on these portals, and if not then how the contribution varies across users, and how it is distributed? Do different users focus on different kinds of activities and play specific roles? In this work, we present a survey of users’ social roles that have been identified on online discussion and Q&A platforms including Usenet newsgroups, Reddit, Stack Exchange, and MOOC forums, as well as on crowdsourced encyclopedias, such as Wikipedia, and Baidu Baike, where users interact with each other through talk pages. We discuss the state of the art on capturing the variety of users roles through different methods including the construction of user network, analysis of content posted by users, temporal analysis of user activity, posting frequency, and so on. We also discuss the available datasets and APIs to collect the data from these platforms for further research. The survey is concluded with open research questions.

scholarly journals Technology-enhanced and game based learning for children with special needs: a systematic mapping study

2021 ◽  
Author(s):  
Jose A. Gallud ◽  
Monica Carreño ◽  
Ricardo Tesoriero ◽  
Andrés Sandoval ◽  
María D. Lozano ◽  
...  
Keyword(s):  
Special Needs ◽  
State Of The Art ◽  
Research Community ◽  
Systematic Mapping Study ◽  
Children With Special Needs ◽  
Game Based Learning ◽  
Mapping Study ◽  
Systematic Mapping ◽  
Wide Range ◽  
Research Questions

AbstractTechnology-based education of children with special needs has become the focus of many research works in recent years. The wide range of different disabilities that are encompassed by the term “special needs”, together with the educational requirements of the children affected, represent an enormous multidisciplinary challenge for the research community. In this article, we present a systematic literature review of technology-enhanced and game-based learning systems and methods applied on children with special needs. The article analyzes the state-of-the-art of the research in this field by selecting a group of primary studies and answering a set of research questions. Although there are some previous systematic reviews, it is still not clear what the best tools, games or academic subjects (with technology-enhanced, game-based learning) are, out of those that have obtained good results with children with special needs. The 18 articles selected (carefully filtered out of 614 contributions) have been used to reveal the most frequent disabilities, the different technologies used in the prototypes, the number of learning subjects, and the kind of learning games used. The article also summarizes research opportunities identified in the primary studies.

scholarly journals Supervised learning for the detection of negation and of its scope in French and Brazilian Portuguese biomedical corpora

2020 ◽  
pp. 1-21 ◽  
Author(s):  
Clément Dalloux ◽  
Vincent Claveau ◽  
Natalia Grabar ◽  
Lucas Emanuel Silva Oliveira ◽  
Claudia Maria Cabral Moro ◽  
...  
Keyword(s):  
Machine Learning ◽  
Information Extraction ◽  
State Of The Art ◽  
Automatic Detection ◽  
Brazilian Portuguese ◽  
Supervised Machine Learning ◽  
Biomedical Domain ◽  
Learning Approaches ◽  
Cross Domain ◽  
Automatic Methods

Abstract Automatic detection of negated content is often a prerequisite in information extraction systems in various domains. In the biomedical domain especially, this task is important because negation plays an important role. In this work, two main contributions are proposed. First, we work with languages which have been poorly addressed up to now: Brazilian Portuguese and French. Thus, we developed new corpora for these two languages which have been manually annotated for marking up the negation cues and their scope. Second, we propose automatic methods based on supervised machine learning approaches for the automatic detection of negation marks and of their scopes. The methods show to be robust in both languages (Brazilian Portuguese and French) and in cross-domain (general and biomedical languages) contexts. The approach is also validated on English data from the state of the art: it yields very good results and outperforms other existing approaches. Besides, the application is accessible and usable online. We assume that, through these issues (new annotated corpora, application accessible online, and cross-domain robustness), the reproducibility of the results and the robustness of the NLP applications will be augmented.

scholarly journals Leadership Should or Should Not Delegate Communication? (A Systematic Literature review: The Art of Delegation)

2021 ◽  
Vol 15 (2) ◽  
pp. 67-78
Author(s):  
Gibriel Badjie
Keyword(s):  
Literature Review ◽  
Leadership Style ◽  
Systematic Literature Review ◽  
Relevant Research ◽  
Topic Area ◽  
Policy Information ◽  
Research Questions

Communication and delegation are two important and parts of the leadership function. However, it is still a matter of debate whether leaders can delegate responsibility for communication, especially policy information, to those under their authority. Various opinions state that there is no prohibition for leaders to delegate their responsibilities because this is the leader's prerogative. This study aims to identify whether leadership should or should not delegate communication. The method used in this study was Systematic Literature Review (SLR). The SLR method is used to identify, review, evaluate, and interpret all available research by topic area phenomenon of interest, with specific relevant research questions. The results showed that leaders can delegate communication but it is highly dependent on the type, style, and approach of leadership on the table at that time. Such a leadership style or approach will automatically influence the style and approach of communication and delegation.

scholarly journals Survey on serverless computing

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Hassan B. Hassan ◽  
Saman A. Barakat ◽  
Qusay I. Sarhan
Keyword(s):  
Research Evidence ◽  
State Of The Art ◽  
Future Research ◽  
Research Papers ◽  
Systematic Survey ◽  
Server Side ◽  
Large Influence ◽  
Research Questions ◽  
Reducing Costs

AbstractServerless computing has gained importance over the last decade as an exciting new field, owing to its large influence in reducing costs, decreasing latency, improving scalability, and eliminating server-side management, to name a few. However, to date there is a lack of in-depth survey that would help developers and researchers better understand the significance of serverless computing in different contexts. Thus, it is essential to present research evidence that has been published in this area. In this systematic survey, 275 research papers that examined serverless computing from well-known literature databases were extensively reviewed to extract useful data. Then, the obtained data were analyzed to answer several research questions regarding state-of-the-art contributions of serverless computing, its concepts, its platforms, its usage, etc. We moreover discuss the challenges that serverless computing faces nowadays and how future research could enable its implementation and usage.

scholarly journals An investigation of linguistic problems in automatic multi-document summaries / Uma investigação de problemas linguísticos em sumários automáticos multidocumento

2021 ◽  
Vol 29 (2) ◽  
pp. 859
Author(s):  
Márcio De Souza Dias ◽  
Ariani Di Felippo ◽  
Amanda Pontes Rassi ◽  
Paula Cristina Figueira Cardoso ◽  
Fernando Antônio Asevedo Nóbrega ◽  
...  
Keyword(s):  
State Of The Art ◽  
Brazilian Portuguese ◽  
Source Material ◽  
Corpus Annotation ◽  
Automatic Summarization ◽  
Document Summarization ◽  
Art Methods ◽  
Characterization Studies ◽  
Linguistic Problem ◽  
Support Research

Abstract: Automatic summaries commonly present diverse linguistic problems that affect textual quality and thus their understanding by users. Few studies have tried to characterize such problems and their relation with the performance of the summarization systems. In this paper, we investigated the problems in multi-document extracts (i.e., summaries produced by concatenating several sentences taken exactly as they appear in the source texts) generated by systems for Brazilian Portuguese that have different approaches (i.e., superficial and deep) and performances (i.e., baseline and state-of-the art methods). For that, we first reviewed the main characterization studies, resulting in a typology of linguistic problems more suitable for multi-document summarization. Then, we manually annotated a corpus of automatic multi-document extracts in Portuguese based on the typology, which showed that some of linguistic problems are significantly more recurrent than others. Thus, this corpus annotation may support research on linguistic problems detection and correction for summary improvement, allowing the production of automatic summaries that are not only informative (i.e., they convey the content of the source material), but also linguistically well structured.Keywords: automatic summarization; multi-document summary; linguistic problem; corpus annotation.Resumo: Sumários automáticos geralmente apresentam vários problemas linguísticos que afetam a sua qualidade textual e, consequentemente, sua compreensão pelos usuários. Alguns trabalhos caracterizam tais problemas e os relacionam ao desempenho dos sistemas de sumarização. Neste artigo, investigaram-se os problemas em extratos (isto é, sumários produzidos pela concatenação de sentenças extraídas na íntegra dos textos-fonte) multidocumento em Português do Brasil gerados por sistemas que apresentam diferentes abordagens (isto é, superficial e profunda) e desempenho (isto é, métodos baseline e do estado-da-arte). Para tanto, as principais caracterizações dos problemas linguísticos em sumários automáticos foram investigadas, resultando em uma tipologia mais adequada à sumarização multidocumento. Em seguida, anotou-se manualmente um corpus de extratos com base na tipologia, evidenciando que alguns tipos de problemas são significativamente mais recorrentes que outros. Assim, essa anotação gera subsídios para as tarefas automáticas de detecção e correção de problemas linguísticos com vistas à produção de sumários automáticos não só mais informativos (isto é, que cobrem o conteúdo do material de origem), como também linguisticamente bem-estruturados.Palavras-chave: sumarização automática; sumário multidocumento; problema linguístico; anotação de corpus.

scholarly journals Machine Learning for Landslides Prevention: A Survey

2020 ◽  
Author(s):  
Zhengjing Ma ◽  
Gang Mei
Keyword(s):  
Machine Learning ◽  
State Of The Art ◽  
Human Life ◽  
Machine Learning Algorithms ◽  
Warning Systems ◽  
Negative Effects ◽  
Relevant Research ◽  
Related Information ◽  
Urgent Task ◽  
Comprehensive Survey

Landslides are one of the most critical categories of natural disasters worldwide and induce severely destructive outcomes to human life and the overall economic system. To reduce its negative effects, landslides prevention has become an urgent task, which includes investigating landslide-related information and predicting potential landslides. Machine learning is a state-of-the-art analytics tool that has been widely used in landslides prevention. This paper presents a comprehensive survey of relevant research on machine learning applied in landslides prevention, mainly focusing on (1) landslides detection based on images, (2) landslides susceptibility assessment, and (3) the development of landslide warning systems. Moreover, this paper discusses the current challenges and potential opportunities in the application of machine learning algorithms for landslides prevention.

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