Navigation

apoios-header

 

Universidade da Beira Interior

 

INESC Tecnologia e Ciência - INESC TEC

 

Outsystems

 

Dimension Data

 

MaxData-Healthcare Solutions
 

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. 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.

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, 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
  • Ontologies, including but not limited to:
    • Formalisms
    • Modeling
    • Ontology Engineering
    • Semantic Model-driven Engineering
    • Applying explicit semantics to traditional information systems
    • Other explicit semantic models
  • Information Retrieval, 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
  • Data Management, 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

Program Committee

  • Helena Galhardas, Lisbon Technical University, Portugal (coordinator)
  • Paulo Maio, School of Engineering - Polytechnic of Porto, Portugal (coordinator)
  • Rui Camacho, Faculty of Engineering of the University of Porto, Portugal (coordinator)
  • Alberto Simões, University of Minho, Portugal
  • Bruno Martins, Lisbon Technical University, Portugal
  • Carlos Ferreira, School of Engineering - Polytechnic of Porto, Portugal
  • Carlos Soares, Faculty of Engineering of the University of Porto, Portugal
  • Cristina Ribeiro, Faculty of Engineering of the University of Porto, Portugal
  • David Matos, Lisbon Technical University, Portugal
  • Diana Santos, University of Oslo, Norway
  • Fernando Batista, ISCTE - Lisbon University Institute, Portugal
  • Francisco Couto, University of Lisbon, Portugal
  • Hugo Gonçalo Oliveira, University of Coimbra, Portugal
  • Irene Rodrigues, University of Évora, Portugal
  • João Dias Pereira, Lisbon Technical University, Portugal
  • João Magalhães, Faculty of Science and Technology of University of Lisbon, Portugal
  • João Paulo Cordeiro, University of Beira Interior, Portugal
  • João Pedro Silva, Tebe SA, Portugal
  • Jorge Barbosa, Faculty of Engineering of the University of Porto, Portugal
  • Luis Teixeira, Faculty of Engineering of the University of Porto, Portugal
  • Luísa Coheur, Lisbon Technical University, Portugal
  • Nuno Mamede, Lisbon Technical University, Portugal
  • Nuno Silva, School of Engineering - Polytechnic of Porto, Portugal
  • Paulo Gomes, University of Coimbra, Portugal
  • Paulo Novais, University of Minho, Portugal
  • Paulo Oliveira, School of Engineering - Polytechnic of Porto, Portugal
  • Paulo Quaresma, University of Évora, Portugal
  • Pável Calado, Lisbon Technical University, Portugal (coordinator)
  • Ricardo Ribeiro, ISCTE - Lisbon University Institute, Portugal (coordinator)
  
Acções do Documento
organizacao-header

 

Universidade da Beira Interior

 

Faculdade de Ciências da Universidade do Porto

 

Instituto Superior Técnico

 

INESC Tecnologia e Ciência - INESC TEC

 

Inesc ID Lisboa

 

 
Sections