Detail publikace

Knowledge Discovery in Data with FIT-Miner

ŠEBEK, M. HLOSTA, M. ZENDULKA, J.

Originální název

Knowledge Discovery in Data with FIT-Miner

Anglický název

Knowledge Discovery in Data with FIT-Miner

Jazyk

en

Originální abstrakt

The paper deals with a data mining system FIT-Miner that has been developed at the Faculty of Information Technology of the Brno University of Technology. The system is based on a component approach where the essential functionality is encapsulated in components. A data mining task is specified graphically as a network of interconnected components. This approach makes good maintainability and scalability possible. The FIT-Miner includes components for data preprocessing, data mining and presentation of results. Implemented data mining algorithms cover all typically mined kinds of knowledge, such as frequent patterns, association rules; and classification, prediction and clustering models.

Anglický abstrakt

The paper deals with a data mining system FIT-Miner that has been developed at the Faculty of Information Technology of the Brno University of Technology. The system is based on a component approach where the essential functionality is encapsulated in components. A data mining task is specified graphically as a network of interconnected components. This approach makes good maintainability and scalability possible. The FIT-Miner includes components for data preprocessing, data mining and presentation of results. Implemented data mining algorithms cover all typically mined kinds of knowledge, such as frequent patterns, association rules; and classification, prediction and clustering models.

Dokumenty

BibTex


@inproceedings{BUT76267,
  author="Michal {Šebek} and Martin {Hlosta} and Jaroslav {Zendulka}",
  title="Knowledge Discovery in Data with FIT-Miner",
  annote="The paper deals with a data mining system FIT-Miner that has been developed at
the Faculty of Information Technology of the Brno University of Technology. The
system is based on a component approach where the essential functionality is
encapsulated in components. A data mining task is specified graphically as
a network of interconnected components. This approach makes good maintainability
and scalability possible. The FIT-Miner includes components for data
preprocessing, data mining and presentation of results. Implemented data mining
algorithms cover all typically mined kinds of knowledge, such as frequent
patterns, association rules; and classification, prediction and clustering
models.",
  address="VŠB-Technical University of Ostrava",
  booktitle="Znalosti 2011: Sborník příspěvků 10. ročníku konference",
  chapter="76267",
  edition="NEUVEDEN",
  howpublished="print",
  institution="VŠB-Technical University of Ostrava",
  year="2011",
  month="february",
  pages="182--193",
  publisher="VŠB-Technical University of Ostrava",
  type="conference paper"
}