Universidade de Évora

















Data and Knowledge Management

Data and Knowledge Management

(versão PT)

Motivation and Goals

Digital data storage is nowadays a common practice. Besides being vital to organizations and individuals, the existing amount of digital data has significantly increased, and even further growth is expected in the near future. Therefore, there is no doubt about the importance of effectively, efficiently, and safely managing all digitally stored information. This fact has led to the appearance of several scientific research disciplines that concern with problems arising from the need for electronic data management and processing. These disciplines address such problems at different levels:

At a first level, there is the management of the data, where the main concerns are large-scale data storage, data maintenance, quick access to the data, safety and consistency. At a second level, we have information processing. In this case, problems to be solved include data organization according to its information content, extraction of frequent patterns in the data, or searching for information on certain topics. At a third level, we have information interpretation and its translation to human understanding. Digitally stored textual documents can, for example, be feed into natural language processing tools, which can be used to translate the content into different languages, ​​or use the content to answer questions posed by users. Finally, we have the need to represent and share the semantics of the data, either captured by the previous methods or made explicit through ontologies and other semantic models. Problems here are related to exploring such semantics in the context of heterogeneous and decentralized systems, thus supporting processes (emergent or predefined) making use of the available information.

This INForum track aims to present and disseminate research studies coming from different fields related with data and knowledge management.

Topics of Interest

  • Natural Language Processing:
    • Morphology / Syntax / Semantics
    • Language resources
    • Processing speech and textual information
    • Summarization and natural language generation
    • Question/Answer systems
    • Dialog systems
    • Machine translation
  • Information Extraction:
    • Segmentation
    • Classification and disambiguation
    • Association discovery
    • Sentiment analysis
    • Entity/Event discovery
    • Web data extraction
    • Textual information processing
  • Ontologies:
    • Formalisms
    • Modeling
    • Ontology engineering
    • Semantic model-driven engineering
    • Applying explicit semantics to traditional information systems
    • Other explicit semantic models
  • Information Retrieval
    • Information search
    • Indexing and efficient processing of textual and multimedia information
    • Document classification, filtering, and clustering
    • Web information retrieval
  • Data Management
    • Data cleaning and transformation
    • Data quality audit
    • Data integration
    • Semantic integration
    • Distributed storage
    • Query execution and optimization
  • Applications of all the precedent topics

Program Committee

  • Bruno Martins, Lisbon Technical University/INESC-ID, (coordinator)
  • Paulo Maio, School of Engineering - Polytechnic of Porto, (coordinator)
  • Fernando Batista, ISCTE - Lisbon University Institute and INESC-ID, (coordinator)
  • Pável Calado, Lisbon Technical University (Portugal)
  • Luísa Coheur, Lisbon Technical University (Portugal)
  • João Paulo Cordeiro, University of Beira-Interior (Portugal)
  • Francisco Couto, University of Lisbon (Portugal)
  • Helena Galhardas, Lisbon Technical University (Portugal)
  • Paulo Gomes, University of Coimbra (Portugal)
  • Miguel Grade, Maisis Lda.
  • Nuno Mamede, Lisbon Technical University (Portugal)
  • David Matos, Lisbon Technical University (Portugal)
  • Paulo Novais, University of Minho (Portugal)
  • Hugo Gonçalo Oliveira, University of Coimbra (Portugal)
  • Paulo Oliveira School of Engineering - Polytechnic of Porto
  • João Dias Pereira, Lisbon Technical University
  • Paulo Quaresma, University of Évora (Portugal)
  • Irene Rodrigues, University of Évora (Portugal)
  • Diana Santos, University of Oslo (Norway)
  • João Pedro Silva, Tebe SA
  • Nuno Silva, School of Engineering - Polytechnic of Porto
  • Alberto Simões, University of Minho (Portugal)
  • António Lucas Soares, University of Porto (Portugal)
  • Ricardo Daniel Ribeiro, ISCTE - Lisbon University Institute (Portugal)
Acções do Documento
« Julho 2020 »