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9. Marcelo Tibau, Sean Wolfgand Matsui Siqueira, and Bernardo Pereira Nunes. 2020. Semantic Data Structures for Knowledge Generation in Open World Information System. In XVI Brazilian Symposium on Information Systems (SBSI’20), November 3–6, 2020, São Bernardo do Campo, Brazil. ACM, New York, NY, USA 7 Pages.

Abstract: As the amount of information grows exponentially online, Information Systems role in support knowledge flows encouraged by linked data increases as a driver to innovation, culture, business practices and people behavior. Web search engines are particularly affected by the open world challenges, notably as part of the growing digital ecosystems of networks and platforms of technology, media, and telecommunications (TMT) companies delivering personalized and customized services (e.g. Amazon in retailing, Uber in ride service hailing, food delivery, and bicycle-sharing system, and Airbnb in lodging). To recognize search intent drawn from user’s behavior allows to provide personalized search results. The work presented in this paper has the purpose of exploring methods to represent semantic relationships between concepts indexed by Web search engines in order to aid them recognize search intent and display results that meet the search intent. The performance of two different types of data structures based on entity-centric indexing was compared. The data structures were: a knowledge base that used an entity-centric mapping of Wikipedia categories and the KBpedia Knowledge Graph. Through analysis of entity ranking and linking, we detected that the Knowledge Graph could identify approximately three times more properties and relationships, which increases Web search engines capability to “understand” what is being asked.

8.Teixeira C.P., Tibau M., Siqueira S.W.M., Nunes B.P. (2020) Reordering Search Results to Support Learning. In: Popescu E., Hao T., Hsu TC., Xie H., Temperini M., Chen W. (eds) Emerging Technologies for Education. SETE 2019. Lecture Notes in Computer Science, vol 11984. Springer, Cham.

Abstract: 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 support search engine results reordering based on content suitability to learning purposes. We proceeded on the investigation by selecting some self-proclaimed search literacy experts to answer thoroughly questions about their views on the reordered results. We take into account that literacy expert’s judgment may reveal issues regarded to technical side on learning supported by search tools. Experienced users claimed a preference for reliable sources and direct answers to what they are looking for, as they have exploratory skills to overcome information incompleteness.


7. TIBAU, Marcelo; SIQUEIRA, Sean; NUNES, Bernardo Pereira. A comparison between Entity-Centric Knowledge Base and Knowledge Graph to Represent Semantic Relationships for Searching as Learning Situations. Anais dos Workshops do Congresso Brasileiro de Informática na Educação, [S.l.], p. 823, nov. 2019. ISSN 2316-8889. Disponível em: <>.doi:

Abstract: Searching the web with learning intent, known as Searching as Learning (SaL), consists on learners to use Web search engines as a technology to drive their learning process. However, it may be difficult to users to find out relevant information online due to an inability to accurately specify their information need, a situation known as Anomalous State of Knowledge (ASK). To minimize the ASK situation, the continuous flow of data gathering and interaction between user and the search results could be used by search engines to tailor learning-intent search experience. It requires Web search engines to identify such intent and they may use linked data, Knowledge Bases and Graph Databases in order to recognize the meaning of query terms and keywords and use them to predict learning intent. In order to explore the possibility of semantic data structures to represent knowledge that could aid a learning-driven Web search engine to recognize learning intention from user’s queries, the present paper compared the performance of two different types of data structures based on entity-centric indexing to identify properties and semantic relationships. One was a knowledge base that used a entity-centric mapping of Wikipedia categories and the other was the KBpedia Knowledge Graph. The entity ranking and linking of both were analyzed and we discovered that the knowledge graph could identify about three times more properties and relationships.

6. PINELLI, Cleber; TIBAU, Marcelo; SIQUEIRA, Sean. Google, se reordene e me ajude a aprender: Critérios de relevância para reordenar resultados de busca como um processo de aprendizagem. Brazilian Symposium on Computers in Education (Simpósio Brasileiro de Informática na Educação – SBIE), [S.l.], p. 576, nov. 2019. ISSN 2316-6533. Disponível em: <>. doi:

Abstract: As ferramentas de busca podem auxiliar as pessoas na condução de tarefas de aprendizagem informal, contudo os critérios usados para o ranqueamento de seus resultados estão voltados a prover respostas factuais e pouco processuais. Neste contexto, este artigo apresenta critérios de relevância, baseados em teorias de aprendizagem, para apoiar uma reordenação dos resultados da busca quando há intenção de aprendizado. Para avaliar a aplicabilidade da proposta, foi utilizado um questionário contendo um comparativo entre exemplos de páginas de resultado de busca da Google e sua versão modificada. A pesquisa evidenciou que o resultado reordenado foi melhor aceito, sobretudo por aqueles que possuem maior habilidade de busca. Isto pode ser um indicativo de que reorganizar o resultado de buscas com base em teorias de aprendizagem pode apoiar a aprendizagem informal.

5. M. Tibau, S. W. M. Siqueira, B. Pereira Nunes, T. Nurmikko-Fuller and R. F. Manrique, “Using Query Reformulation to Compare Learning Behaviors in Web Search Engines,” 2019 IEEE 19th International Conference on Advanced Learning Technologies (ICALT), Maceió, Brazil, 2019, pp. 219-223.
doi: 10.1109/ICALT.2019.00054
keywords: {query reformulation;query states;searching as learning;Web search engine;exploratory search;knowledge-intensive process},

Abstract: Web search engines have gained importance as tools capable of connecting informal and self-learning with formal learning by aiding individuals in retrieving relevant information through the formulation and modification of their queries. Understand the differences between query states and their transitions becomes increasingly important, as doing so makes the optimization of search engines’ results according to educational uses and needs possible. This paper introduces the ESKiP Taxonomy of Query States, a classification framework validated in an experiment involving two different query log datasets. It enables the comparison between the behaviors of users in search for knowledge (learners) and users performing transactional or factual searches in Web search engines.

4. Marcelo Tibau, Sean W. M. Siqueira, Fernanda Baião and Bernardo Pereira Nunes. 2018. Exploratory Search as a Knowledge-intensive Process. Euro American Conference on Telematics and Information Systems (EATIS ’18), November 12–15, 2018, Fortaleza, Brazil, 8 pages.

Abstract: 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, human-computer interaction, Web searching and educational technology. The Exploratory Search Knowledge-Intensive Process model considers tasks and search activities as part of a chain of actions that help clarify the reasons why a subject is searched. It also supports the visualization on how the information retrieved is used to define decision criteria about which data is worth extracting, to draw inferences, and to create a shortcut to understanding.


3. ALMEIDA, R. S. ; SIQUEIRA, S.W.M. ; TIBAU, M., QUEIROZ, J.. A Correlation Index Between Two Different Text and Web Resource Classification Systems. In: 9th Euro-American Conference on Telematics and Information Systems (EATIS 2018), 2018, Fortaleza. PProceedings of the Euro American Conference on Telematics and Information Systems. Article No. 43

Abstract: Classifying content on the Web has been a common subject of research, since the amount of available data on the Web, especially in text format, grows every day. In this paper it is proposed a correlation index to measure how close a classification system based on Wikipedia categorization is of a service provided by Watson IBM that has the same purpose: text and resourceclassification on the Web.

DOI: 10.1145/3293614.3293652

2. Tibau, M. ; Siqueira, S.W.M. ; Nunes, B. P. ; Bortoluzzi, M. ; Marenzi, I. ; Kemkes, P. . Investigating users’ decision-making process while searching online and their shortcuts towards understanding. In: 17th International Conference on Web-based Learning, 2018, ChiangMai. Advances in Web-Based Learning (ICWL 2018), 17th International Conference, 2018.

Abstract: This paper presents how we apply Exploratory Search KiP model, a model capable of assisting the visualization of search patterns and identifying best practices associated to users’ decision-making processes, to log analysis and how it helps understand the process and decisions taken while carrying out a search. This study aims to model searches performed through web search tools and educational resources portals, to enable a conceptual framework to support and improve the processes of learning through searches. Applying the model to log analysis, we are able: (1) to see how the information retrieved is used to define decision criteria about which data are worth extracting; (2) to draw inferences and shortcuts to support understanding; (3) to observe how the search intention is modified during search activities; and, (4) to analyze how the purpose that drives the search turned into real actions.


1. Tibau, M., Siqueira, S.W.M., Nunes, B.P., Marenzi, I., Bortoluzzi, M.: Modeling exploratory search as a knowledge-intensive process. In: 2018 Proceedings of the 18th IEEE International Conference on Advanced Learning Technologies (ICALT 2018), Mumbai. IEEE, New York (2018).

Abstract: Searching as Learning and Information Seeking require exploratory search to be modeled for supporting learning. The present paper introduces a model of exploratory search that was applied on web searching in language teacher education, which promoted its evolution and validation, and enabled a visualization of search pattern and learning process. This model was able to help clarify best practices associated to users’ decision-making process regarding suitable and not suitable information and to capture the relevance of context variables, personal skills and expertise that users utilize as filters for the search.

DOI: 10.1109/ICALT.2018.00015

MASTER THESIS: Understanding web search patterns through exploratory search as a knowledge-intensive Process. [PDF]. MTV Dias – 2019 –

Abstract: As data grows exponentially and the Web encompasses most part of the knowledge Human Beings create the seeking for intelligent information systems capable of going beyond keyword searches increases …

Resumo: À medida em que os dados na Web crescem exponencialmente e abrangem a maior parte do conhecimento produzido pela humanidade, a busca por sistemas de informação inteligentes capazes de irem além das buscas por palavras-chave aumenta …


LIVRO: Conexão do Conhecimento – Conectar para gerar ideias, inovações e aprendizado

Por: R$ 40,43   (ebook: R$ 20,21)
ISBN: 978- 85-7773-840-3   ISBN (ebook): 644-00-0000-002-4
Formato: 14×21
N° de páginas: 156

Estamos em uma nova era da história da humanidade, saímos da Idade Contemporânea e entramos na Idade do Conhecimento. Ela se define por um fato muito simples, é cada vez mais fácil gerar algum tipo de conhecimento e distribuí-lo. Portanto, as pessoas, empresas e países que irão se destacar, serão aquelas que criarem consistentemente propriedade intelectual, conhecimento aplicável. Ao contrário do que se possa imaginar, o que vai crescer não é o conceito do Gerenciamento de Conhecimento e sim o da Conexão do Conhecimento, mesmo porque conhecimento não se gerencia, se difunde. O fato é que uma pessoa só vai compartilhar a sua experiência, que é o que a faz importante individualmente, se achar que vai contribuir e muito para a sua vida. E outra pessoa só vai querer aprender o conhecimento compartilhado por alguém, se este for relevante pra ela. Isso é Conexão e é sobre ela que se trata este livro.

Para comprar, clique no logo da editora (impresso) ou no logo do site Kobo (ebook):

publit     Sem Título-9


IMAGENS E ESQUEMAS: Conexão do Conhecimento 

Imagens e esquemas constantes no livro Conexão do Conhecimento – Conectar para gerar ideias, inovações e aprendizado em um arquivo pdf. O download do arquivo é gratuito, para tal basta clicar no ícone abaixo.




A Era da Inovação 

Análise do estudo de Robert J. Gordon a respeito do constante fluxo de inovação que revolucionou o modo de vida do mundo entre 1870 e 1970. O download do arquivo é gratuito, para tal basta clicar no ícone abaixo.




Learning Analytics

Infográfico com o processo do modelo Learning Analytics. Disponibilizado originalmente por OpenColleges e adaptado para o português por O download do arquivo é gratuito, para tal basta clicar no ícone abaixo.




Flipped Classroom / Project-Based Learning 

kit de infográficos com 2 modelos educacionais: Flipped ClassroomProject-Based Learning. O primeiro, estimula o desenvolvimento do pensamento crítico (que é entender o mundo à volta e a sua relação com ele) e o segundo, o pensamento reflexivo (criar algo novo a partir do seu conhecimento). Os infográficos trazem o passo a passo de implementação dos 2 modelos.



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