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Maxdata

 

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Data and Knowledge Management


(Versão Portuguesa)

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 nodoubt 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. Similarly to international forums such as the ACM International Conference on Information and Knowledge Management, this track aims at joining, in a single event, several communities, such as those of researchers and professionals in the areas of Databases, Data Mining, Information Retrieval, Knowledge Management, Natural Language Processing and Ontologies, whose scientific work can be complementary in solving currently important problems.

The aim of this session is to disseminate works from these areas as well as to foster a forum for the discussion and exchange of knowledge and practices between researchers and professionals, focusing in the rapid and holistic adoption of multidisciplinary methods and techniques. The authors should submit original work related with the session topics. Twotypes of submissions will be accepted: (1) papers, presenting results of scientific research work carried out in an academic or industrial context. These papers should be written in Portuguese or English and will be evaluated by the Program Committee; and (2) communications, which are intended to enable the dissemination of non-scientific work, that results from an informal form of R&D;, developed in the community. The communications will be selected by the Program Committee and should be submitted as extended abstracts.

Papers and communications will be presented orally, being that communications will have a shorter presentation time than papers. All accepted submissions can alsobe presented in the exhibition space. The authors can have a poster and/or make a demonstration of tools. The proceedings of this session shall only contain papers written in the Springer LNCS format, with nomore than twelve pages. Communications must alsofollow the Springer LNCS format and should have nomore than four pages.

Topics of Interest

  • NaturalLanguageProcessing, including but not limited to:
    • Morphology/Syntax/Semantics
    • Language resources
    • Processing speech and textual information
    • Summarization and natural language generation
    • Question/Answer systems
    • Dialog systems
    • Machine translation
  • Information Extraction, including but not limited to:
    • Segmentation
    • Classification and disambiguation
    • Sentiment analysis
    • Entity/Event discovery
    • Web data extraction
  • Knowledge Extraction, including but not limited to:
    • Data Source Heterogeneity (e.g. transactional/relational, web, text, graphs, images)
    • Tasks (e.g. clustering, frequent patterns, classification, anomaly detection)
    • Architectures and/or infrastructures
    • Tools
    • Challenges in Big Data
    • Deep Learning
    • Autonomous Systems
  • Ontologies, including but not limited to:
  • Formalisms
    • Modelling
    • Ontology Engineering
    • Semantic Model-Driven Engineering
    • Applying explicit semantics
    • traditional information systems
    • Other explicit semantic models
  • InformationRetrieval, including but not limited to:
    • Information search
    • Indexing and efficient processing of textual and multimedia information
    • Machine Learning applied to information retrieval
    • Web information retrieval
    • Online social network analysis
  • DataManagement, including but not limited to:
    • Data cleaning and transformation
    • Data quality audit
    • Data integration
    • Semantic integration
    • Distributed storage
    • Query execution and optimization
  • Applications of all the precedent topics

Organization

  • Carlos Ferreira, Laboratory of Artificial Intelligence and Decision Support - INESC Tec, Portugal
  • NunoBettencourt, Polytechnic of Porto, Portugal

Program Committee

  • Alberto Simões, University of Minho, Portugal
  • Cristina Ribeiro, University of Porto, Portugal
  • David Martins de Matos, University of Lisbon, Portugal
  • Diana Santos, University of Oslo, Norway
  • Eduardo Marques, University of Porto, Portugal
  • Elsa Gomes, Polytechnic of Porto, Portugal
  • Fernando Batista, ISCTE-UniversityInstitute of Lisbon, Portugal
  • Francisco Couto, University of Lisbon, Portugal
  • Helena Galhardas, University of Lisbon, Portugal
  • Irene Rodrigues, UniversityofEvora, Portugal
  • João Dias Pereira, University of Lisbon, Portugal
  • João Paulo Cordeiro, UniversityofBeiraInterior, Portugal
  • Jorge Barbosa, University of Porto, Portugal
  • Jorge Coelho, Polytechnic of Porto, Portugal
  • Miguel Areias, University of Porto, Portugal
  • Nuno Mamede, University of Lisbon, Portugal
  • Nuno Silva, Polytechnic of Porto, Portugal
  • Paulo Maio, Polytechnic of Porto, Portugal
  • Paulo Novais, University of Minho, Portugal
  • Paulo Oliveira, Polytechnic of Porto, Portugal
  • Paulo Quaresma, UniversityofEvora, Portugal
  • Pável Calado, University of Lisbon, Portugal
  • Pedro Ferreira, University of Porto, Portugal
  • Ricardo Ribeiro, ISCTE-University Institute of Lisbon, Portugal
  • Ricard Rocha, University of Porto, Portugal
  • Rita Ribeiro, University of Porto, Portugal
  • Rui Camacho,University of Porto, Portugal
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Universidade de Coimbra
 
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