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About

I was born in Portugal in 1964. I graduated in mathematics from the Faculty of Sciences of the University of Porto and earned a Ph.D. in Computer Science from the same institution.
My current position is auxiliary professor at the Computer Science department of the Faculty of Sciences of the University of Porto. I am also affiliated with the Center for Research in Advanced Computing Systems (CRACS), an R&D unit of INESCTEC Research Laboratory, where I am an effective member.
My main research interests are technology enhanced learning, web adaptability, and semantic web.

Interest
Topics
Details

Details

  • Name

    José Paulo Leal
  • Cluster

    Computer Science
  • Role

    Senior Researcher
  • Since

    01st January 2009
002
Publications

2020

Visualization of path patterns in semantic graphs

Authors
Leal, JP;

Publication
COMPUTER SCIENCE AND INFORMATION SYSTEMS

Abstract
Graphs with a large number of nodes and edges are difficult to visualize. Semantic graphs add to the challenge since their nodes and edges have types and this information must be mirrored in the visualization. A common approach to cope with this difficulty is to omit certain nodes and edges, displaying sub-graphs of smaller size. However, other transformations can be used to summarize semantic graphs and this research explores a particular one, both to reduce the graph's size and to focus on its path patterns. A-graphs are a novel kind of graph designed to highlight path patterns using this kind of summarization. They are composed of a-nodes connected by a-edges, and these reflect respectively edges and nodes of the semantic graph. A-graphs trade the visualization of nodes and edges by the visualization of graph path patterns involving typed edges. Thus, they are targeted to users that require a deep understanding of the semantic graph it represents, in particular of its path patterns, rather than to users wanting to browse the semantic graph's content. A-graphs help programmers querying the semantic graph or designers of semantic measures interested in using it as a semantic proxy. Hence, a-graphs are not expected to compete with other forms of semantic graph visualization but rather to be used as a complementary tool. This paper provides a precise definition both of a-graphs and of the mapping of semantic graphs into a-graphs. Their visualization is obtained with a-graphs diagrams. A web application to visualize and interact with these diagrams was implemented to validate the proposed approach. Diagrams of well-known semantic graphs are presented to illustrate the use of agraphs for discovering path patterns in different settings, such as the visualization of massive semantic graphs, the codification of SPARQL or the definition of semantic measures. The validation with large semantic graphs is the basis for a discussion on the insights provided by a-graphs on large semantic graphs: the difference between a-graphs and ontologies, path pattern visualization using a-graphs and the challenges posed by large semantic graphs.

2020

Authoring Game-Based Programming Challenges to Improve Students’ Motivation

Authors
Paiva, JC; Leal, JP; Queirós, R;

Publication
Advances in Intelligent Systems and Computing

Abstract
One of the great challenges in programming education is to keep students motivated while working on their programming assignments. Of the techniques proposed in the literature to engage students, gamification is arguably the most widely spread and effective method. Nevertheless, gamification is not a panacea and can be harmful to students. Challenges comprising intrinsic motivators of games, such as graphical feedback and game-thinking, are more prone to have longterm positive effects on students, but those are typically complex to create or adapt to slightly distinct contexts. This paper presents Asura, a game-based programming assessment environment providing means to minimize the hurdle of building game challenges. These challenges invite the student to code a Software Agent to solve a certain problem, in a way that can defeat every opponent. Moreover, the experiment conducted to assess the difficulty of authoring Asura challenges is described. © 2020, Springer Nature Switzerland AG.

2019

Estimating time and score uncertainty in generating successful learning paths under time constraints

Authors
Nabizadeh, AH; Jorge, AM; Leal, JP;

Publication
Expert Systems

Abstract

2019

Quarmic: A data-driven web development framework

Authors
Pereira Cunha, PM; Leal, JP;

Publication
OpenAccess Series in Informatics

Abstract
Quarmic is a web framework for rapid prototyping of web applications. Its main goal is to facilitate the development of web applications by providing a high level of abstraction that hides Web communication complexities. This framework allows developers to build scalable applications capable of handling data communication in different models, data persistence and authentication, requiring them just to use simple annotations. Quarmic’s approach consists of the replication of the shared object among clients and server in order to communicate through its methods execution. Where the annotations, namely decorators, are used to indicate the concern (model or view) that each method addresses and to implement the framework’s inversion of control. By indicating the method concern, it enables the separation of its execution across the clients (responsible for the view) and the server (responsible for the model) which facilitates the state management and code maintenance. © Pedro M. P. Cunha and José P. Leal.

2018

EmoSpell, a morphological and emotional word analyzer

Authors
Maia, MI; Leal, JP;

Publication
Information (Switzerland)

Abstract
The analysis of sentiments, emotions, and opinions in texts is increasingly important in the current digital world. The existing lexicons with emotional annotations for the Portuguese language are oriented to polarities, classifying words as positive, negative, or neutral. To identify the emotional load intended by the author, it is necessary to also categorize the emotions expressed by individual words. EmoSpell is an extension of a morphological analyzer with semantic annotations of the emotional value of words. It uses Jspell as the morphological analyzer and a new dictionary with emotional annotations. This dictionary incorporates the lexical base EMOTAIX.PT, which classifies words based on three different levels of emotions-global, specific, and intermediate. This paper describes the generation of the EmoSpell dictionary using three sources: the Jspell Portuguese dictionary and the lexical bases EMOTAIX.PT and SentiLex-PT. Additionally, this paper details the Web application and Web service that exploit this dictionary. It also presents a validation of the proposed approach using a corpus of student texts with different emotional loads. The validation compares the analyses provided by EmoSpell with the mentioned emotional lexical bases on the ability to recognize emotional words and extract the dominant emotion from a text. © 2018 by the authors.

Supervised
thesis

2017

Avaliação de diagramas no Mooshak 2.0

Author
Helder Patrick de Pina Correia

Institution
UP-FCUP

2017

EmoSpell, an Emotional Word Analyser

Author
Maria Inês Ferreira da Costa Maia

Institution
UP-FCUP

2017

Uma abordagem para evoluir sistemas web legado para web services

Author
Revailton de Souza Castro Junior

Institution
UP-FCUP

2016

Long term goal oriented recommender system

Author
Amir Hossein Nabizadeh Rafsanjani

Institution
UP-FCUP

2016

Integração e processamento de dados em experiências sobre processos cognitivos da escrita

Author
Patrícia Sofia Borges Santos

Institution
UP-FCUP