Using Ontologies in Semantic Data Mining with SEGS and g-SEGS

  • Nada Lavrač
  • Anže Vavpetič
  • Larisa Soldatova
  • Igor Trajkovski
  • Petra Kralj Novak
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6926)


With the expanding of the Semantic Web and the availability of numerous ontologies which provide domain background knowledge and semantic descriptors to the data, the amount of semantic data is rapidly growing. The data mining community is faced with a paradigm shift: instead of mining the abundance of empirical data supported by the background knowledge, the new challenge is to mine the abundance of knowledge encoded in domain ontologies, constrained by the heuristics computed from the empirical data collection. We address this challenge by an approach, named semantic data mining, where domain ontologies define the hypothesis search space, and the data is used as means of constraining and guiding the process of hypothesis search and evaluation. The use of prototype semantic data mining systems SEGS and g-SEGS is demonstrated in a simple semantic data mining scenario and in two real-life functional genomics scenarios of mining biological ontologies with the support of experimental microarray data.


Semantic data mining ontologies background knowledge relational data mining 


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© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Nada Lavrač
    • 1
    • 2
  • Anže Vavpetič
    • 1
  • Larisa Soldatova
    • 3
  • Igor Trajkovski
    • 4
  • Petra Kralj Novak
    • 1
  1. 1.Department of Knowledge TechnologiesJožef Stefan InstituteLjubljanaSlovenia
  2. 2.University of Nova GoricaNova GoricaSlovenia
  3. 3.Aberystwyth UniversityWalesUnited Kingdom
  4. 4.Faculty of Electrical Engineering and Information TechnologiesSs. Cyril and Methodius UniversitySkopjeMacedonia

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