Bernardo Pereira Nunes

Australian National University | ANU · Research School of Computer Science

This survey investigates the multifaceted nature of forgetting in machine learning, drawing insights from neuroscientific research that posits forgetting as an adaptive function rather than a defect, enhancing the learning process and preventing overfitting. This survey focuses on the benefits of forgetting and its applications across various machi...

Predicting student engagement can provide timely feedback and help teachers make adjustments to their practices to meet student needs and improve their learning experience. This paper proposes (i) a 4-step approach using a sequential ensemble model for engagement prediction; (ii) discusses the contribution of different features to the model and the...

Humans' ability to transfer knowledge through teaching is one of the essential aspects for human intelligence. A human teacher can track the knowledge of students to customize the teaching on students’ needs. With the rise of online education platforms, there is a similar need for machines to track the knowledge of students and tailor their learnin...

Preventing student dropout is a challenge for higher education institutions (HEIs) that have worsened with COVID-19 and online classes. Despite several research attempts to understand and reduce dropout rates in HEIs, the solutions found in the literature are often hardcoded, making reuse difficult and therefore slowing progress in the area. In an...

Semantic technologies are evolving and being applied in several research areas, including the education domain. This paper aims to present the results of a systematic review carried out to provide an overview of the application of Semantic technologies in the context of the Computer Science curriculum and discuss the limitations in this field whils...

The COVID-19 pandemic has created enormous challenges for society due to the various ways of impacting health. This paper focuses on the impact of the COVID-19 pandemic on people's food consumption patterns in the online environment. We investigate food app reviews and examine whether countries with a high rate of success with COVID-19 control cons...

Humans ability to transfer knowledge through teaching is one of the essential aspects for human intelligence. A human teacher can track the knowledge of students to customize the teaching on students needs. With the rise of online education platforms, there is a similar need for machines to track the knowledge of students and tailor their learning...

Knowing the level of complexity of digital resources is crucial to delimit their use in the educational context. This paper summarizes the contributions of my thesis and focuses on strategies to build conceptual networks based on the content of digital resources; identifying metrics and features to measure complexity in conceptual networks accurate...

This paper describes an experiment that uses Concurrent Think-Aloud protocol (CTA) and person-to-person interviews to map searching behaviors and knowledge flows during search sessions. The findings are: (1) the most used searching strategy during exploratory searches was the “Metacognitive Domain”; and (2) online searching experts have a fair abil...

Aprender ao longo da vida através de ambientes pessoais de aprendizagem O que pensa de aprender ao longo da vida? Muitos de nós descrevemo-nos com termos que moldam a nossa identidade. É comum ouvir pessoas dizer "eu sou músico", e esse comportamento confere à pessoa uma sensação de pertença a algum grupo. Outros preferem descrever-se através das s...

To better understand users’ intent, Web search engines need to transcend its information sorter utility and acquire a more relevant ability concerning semantics’ discernment. This master thesis presents the Exploratory Search KiP model, which helps clarify the reasons why a subject is searched and supports the visualization of decision criteria use...

Personalization algorithms play an essential role in the way search platforms fetch results to users. While there are many empirical studies about the effects of these algorithms on Web searches like Google and Bing, reports about personalization on social media searches are rare. This exploratory study aims to understand and quantify the limits of...

This article presents an in-depth analysis and comparison of two computer science degree offerings, viz.. The analysis is based on the student transcripts collected from the academic systems of both institutions over circa one decade. The article starts with a description of the degrees and global statistics of the student population considered. Th...

Although many learning activities involve search engines, their ranking criteria are focused on providing factual rather than procedural information. In the context of Searching as Learning, providing factual information may not be the best approach. In this paper, we discuss the relevance criteria according to traditional learning theories to supp...

Objetivo do Capítulo Este capítulo tem o objetivo de apresentar o conceito de crowdsourcing bem como uma reflexão sobre os fatores-chave a serem considerados em experimentos que exijam inteligência humana em larga escala. Ao final da leitura deste capítulo, você deve ser capaz de: • Conhecer um novo paradigma de avaliações baseada em crowdsourcing....

Learning basic concepts before complex ones is a natural form of learning. Automated systems and instructional designers evaluate and order concepts’ complexity to successfully generate and recommend or adapt learning paths. This paper addresses the specific challenge of accurately and adequately identifying concept prerequisites using semantic web...

Purpose Although ontology matchers are annually proposed to address different aspects of the semantic heterogeneity problem, finding the most suitable alignment approach is still an issue. This study aims to propose a computational solution for ontology meta-matching (OMM) and a framework designed for developers to make use of alignment techniques...

This paper reports on an investigation into outstanding and ordinary users of two Question & Answer (Q&A) communities. Considering some behavior perspectives such as participation, linguistic traits, social ties, influence, and focus, we found that outstanding users (i) are more likely to engage in discussions; (ii) tend to use more sophisticated l...

Identifying and monitoring students who are likely to dropout is a vital issue for universities. Early detection allows institutions to intervene, addressing problems and retaining students. Prior research into the early detection of at-risk students has opted for the use of predictive models, but a comprehensive assessment of the suitability of di...

This paper presents an exploratory search model capable of assisting the visualization of search patterns and clarifying best practices associated to users' decision-making process, with implications in areas related to information retrieval, humancomputer interaction, Web searching and educational technology. The Exploratory Search Knowledge-Inten...

A common problem faced by data publishers is how to semantically represent data and how to find vocabularies that best represent their data to publish in the Web. To address these problems, this paper introduces a tool, called VocRec, which can be used for recommending vocabularies for relational data that will be published as Linked Data on the We...

Identifying topics associated with a set of documents is a common task for many applications and can be used to improve various tasks involving documents on the Web, such as search, retrieval, recommendation, and clustering. To address this problem, this paper introduces a tool, called TagTheWeb, as a proposition of a generic classification method,...

Currently available datasets still have a large unexplored potential for interlinking. Ranking techniques contribute to this task by scoring datasets according to the likelihood of finding entities related to those of a target dataset. Ranked datasets can be either manually selected for standalone linking discovery tasks or automatically inspected...

How do important members of online Question & Answer communities (who we call experts) behave? And how do they influence the discussions in which they take part? This work reports on an investigation into these questions, which we answer through analyses exploring metrics, machine learning classifiers, and recommendations. We report on several find...

This paper introduces a new line of investigation into Social Media Mourning (SMM), the act of individual and collective grieving on social media. Previous research has analysed this behaviour as a response to a death within a family unit or amongst a group of friends. We report on SMM in the context of the death of a celebrity. We present a compar...

Linked Data principles and technologies are being investigated in various areas. In the Educational context, many studies are using Linked Data trying to solve problems of interoperability of educational data and resources, enriching educational content, and personalizing and recommending educational content and practices. This article presents a s...

This paper presents a case study of a Mathematics’ regular course offered every academic term to about 1500 STEM students of the Instituto Superior Técnico of Lisbon. The main concern of this course is the low approval rates and the high dropout rates. A new approach, called Online Electronic Quizzes with Random Parameters, based on the formative a...

This article defines, implements, and evaluates techniques to automatically compare and recommend conferences. The techniques for comparing conferences use familiar similarity measures and a new measure based on co-authorship communities, called co-authorship network community similarity index. The experiments reported in the article indicate that...

A knowledge base stores descriptions of entities and their relationships, often in the form of a very large RDF graph, such as DBpedia or Wikidata. The entity relatedness problem refers to the question of computing the relationship paths that better capture the connectivity between a given entity pair. This paper describes a dataset created to supp...

This paper1 first argues that ontology design may benefit from treating ontologies as theories and from the definition of a set of operations that map ontologies into ontologies, especially their constraints. The paper then defines the class of ontologies used and proposes four operations to manipulate them. It proceeds to discuss how the operation...

O uso de Dados Conectados na Educação pode trazer avanços para aárea de Informática na Educação. Entretanto, alguns obstáculos ainda precisam ser superados. Neste artigo nós os discutidos sob diferentes perspectivas, tais como a propriedade e a privacidade dos dados, a necessidade de políticas públicas para incentivar sua abertura e reutilização, a...

This paper investigates expert behaviour in Q&A communities in order to understand their influence in online discussions. Our evaluation shows that experts are more likely to provide help than non-experts, and when they participate in a discussion, the quality and length of the discussions tend to increase. In addition, we propose the usage of two...

Data stream mining is the process of extracting knowledge from massive real-time sequence of data items arriving at a very high data rate. It has several practical applications, such as user behavior analysis, software testing and market research. However, the large amount of data generated may offer challenges to process and analyze data at nearly...

Technological prospection is a formal process to identify, evaluate and interpret an innovation (or an innovation proposal) on a particular domain. This work shows how we planned and executed a study based on technological prospection to check the innovation proposals of virtual environments and technologies used to support education. We found that...

Datasets published on the Web and following the Linked Open Data (LOD) practices have the potential to enrich other LOD datasets in multiple domains. However, the lack of descriptive information, combined with the large number of available LOD datasets, inhibits their interlinking and consumption. Aiming at facilitating such tasks, this paper propo...

The fast growing number of datasets available on the Web inspired researchers to propose innovative techniques to combine spatio-temporal data with contextual data. However, as the number of datasets has increased relatively fast, finding the most appropriate datasets for enrichment also became extremely difficult. This paper proposes an innovative...

A connectivity profile for a pair of entities provides a concise explanation about how the entities are related. This paper describes a tool, called DBpedia Profiler, which implements a strategy to generate connectivity profiles for entities represented in DBpedia. The tool uses SPARQL queries to generate relationship paths and follows a technique...

In the Linked Data field, data publishers frequently materialize linksets between two different datasets using link discovery tools. To create a linkset, such tools typically execute linkage rules that retrieve data from the underlying datasets and apply matching predicates to create the links, in an often complex process. Also, such tools do not s...

This paper first introduces techniques for comparing conferences that use familiar similarity measures and a new measure based on co-authorship communities. Then, it focuses on two families of techniques for conference recommendation, the first one based on the similarity measures and the second on the idea of finding the most related authors in th...

An analysis of the proceedings of the first decade of the WEBIST conference, in terms of social networking and statistical analyses, as well as bibliometrics, unearthed information regarding existing patterns in the prevalent themes and topics of the conference, shedding light on the development of the event and its community as they grew and matur...

A capacidade de avaliar criticamente informações textuais relativas ao material social, político e outros desempenha um papel crucial nos processos de formação de opinião e de tomada de decisão Ela pode afetar pontos de vista pessoais e até mesmo provocar uma mudança social. Pensado para auxiliar nesse contexto, o jogo ISCOOL fornece ao usuário uma...

Este artigo mostra um estudo exploratorio das colaboracoes realizadas entre pesquisadores de Informatica na Educacao, com base nas publicacoes do Simposio Brasileiro de Informatica na Educacao (SBIE) entre 2001 e 2013. O principal objetivo deste trabalho e entender a colaboracao entre pesquisadores desta comunidade e identificar os temas discutidos...