Using ontologies in semantic data mining with SEGS and g-SEGS

Nada Lavrač, Anže Vavpetič, Larisa Soldatova, Igor Trajkovski, Petra Kralj Novak

Research output: Contribution to Book/Report typesConference contributionpeer-review

Abstract (may include machine translation)

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.

Original languageEnglish
Title of host publicationDiscovery Science - 14th International Conference, DS 2011, Proceedings
Pages165-178
Number of pages14
DOIs
StatePublished - 2011
Externally publishedYes
Event14th International Conference on Discovery Science, DS 2011, Co-located with the 22nd International Conference on Algorithmic Learning Theory, ALT 2011 - Espoo, Finland
Duration: 5 Oct 20117 Oct 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6926 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference14th International Conference on Discovery Science, DS 2011, Co-located with the 22nd International Conference on Algorithmic Learning Theory, ALT 2011
Country/TerritoryFinland
CityEspoo
Period5/10/117/10/11

Keywords

  • Semantic data mining
  • background knowledge
  • ontologies
  • relational data mining

Fingerprint

Dive into the research topics of 'Using ontologies in semantic data mining with SEGS and g-SEGS'. Together they form a unique fingerprint.

Cite this