Using Semantic Data Mining for Classification Improvement and Knowledge Extraction

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2014
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DAMIART
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Core Facility der Universität Konstanz
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Published
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SEIDL, Thomas, ed., Marwan HASSANI, ed., Christian BEECKS, ed.. Proceedings of the 16th LWA Workshops: KDML, IR and FGWM, Aachen, Germany, September 8-10, 2014. CEUR-WS.org, 2014, pp. 150-155. CEUR Workshop Proceedings. 1226
Zusammenfassung

The objective of this position paper is to show that the inte- gration of semantic data mining into the DAMIART data mining system can help further improve classification performance and knowledge ex- traction. DAMIART performs multi-label classification in the presence of multiple class ontologies, hierarchy extraction from multi-labels and concept relation by association rule mining. Whereas DAMIART com- bines knowledge from multiple data sources and multiple class ontologies, the proposed extension should also explore available ontologies over at- tributes. This will allow the system to produce not only more accurate classification results but also improve their interpretability and overcome such problems as data sparseness.

Zusammenfassung in einer weiteren Sprache
Fachgebiet (DDC)
004 Informatik
Schlagwörter
Semantic Data Mining; Classification; Knowledge Extraction
Konferenz
KDML, 8. Sept. 2014 - 12. Sept. 2014, Aachen, Germany
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ISO 690BENITES, Fernando, Elena SAPOZHNIKOVA, 2014. Using Semantic Data Mining for Classification Improvement and Knowledge Extraction. KDML. Aachen, Germany, 8. Sept. 2014 - 12. Sept. 2014. In: SEIDL, Thomas, ed., Marwan HASSANI, ed., Christian BEECKS, ed.. Proceedings of the 16th LWA Workshops: KDML, IR and FGWM, Aachen, Germany, September 8-10, 2014. CEUR-WS.org, 2014, pp. 150-155. CEUR Workshop Proceedings. 1226
BibTex
@inproceedings{Benites2014Using-29338,
  year={2014},
  title={Using Semantic Data Mining for Classification Improvement and Knowledge Extraction},
  number={1226},
  publisher={CEUR-WS.org},
  series={CEUR Workshop Proceedings},
  booktitle={Proceedings of the 16th LWA Workshops: KDML, IR and FGWM, Aachen, Germany, September 8-10, 2014},
  pages={150--155},
  editor={Seidl, Thomas and Hassani, Marwan and Beecks, Christian},
  author={Benites, Fernando and Sapozhnikova, Elena}
}
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