Detail publikace

Intuitive and Interactive Mining

Originální název

Intuitive and Interactive Mining

Anglický název

Intuitive and Interactive Mining

Jazyk

en

Originální abstrakt

In this paper, we propose a framework, internally called OLAM SE, for interactive and intuitive mining of multilevel association, characterization and classification rules. This framework is proposed as an extension of OLAP or an alternative to Han's OLAM. OLAM processes data stored in data cubes structure of which is based on a given conceptual hierarchy. OLAM SE determines minimum support value from user defined cover of data with usage of entropy coding principle. It also automatically determines the maximum threshold to avoid explaining obvious. Major part of data is thus described by frequent patterns. The presentation of results is inspired by UML diagram notation. It is a graph nodes of which are frequent data sets represented as packages including sub packages - data classes or items. Edges represent relations or patterns between packages. These patterns can be interactively explored by the user, who gets a detailed view of attractive ones. Other, possibly interesting, sets are intuitively offered to her. This is well applicable for the characterization and non-naive Bayesian classification.

Anglický abstrakt

In this paper, we propose a framework, internally called OLAM SE, for interactive and intuitive mining of multilevel association, characterization and classification rules. This framework is proposed as an extension of OLAP or an alternative to Han's OLAM. OLAM processes data stored in data cubes structure of which is based on a given conceptual hierarchy. OLAM SE determines minimum support value from user defined cover of data with usage of entropy coding principle. It also automatically determines the maximum threshold to avoid explaining obvious. Major part of data is thus described by frequent patterns. The presentation of results is inspired by UML diagram notation. It is a graph nodes of which are frequent data sets represented as packages including sub packages - data classes or items. Edges represent relations or patterns between packages. These patterns can be interactively explored by the user, who gets a detailed view of attractive ones. Other, possibly interesting, sets are intuitively offered to her. This is well applicable for the characterization and non-naive Bayesian classification.

BibTex


@inproceedings{BUT28581,
  author="Petr {Chmelař} and Lukáš {Stryka}",
  title="Intuitive and Interactive Mining",
  annote="In this paper, we propose a framework, internally called OLAM SE, for interactive
and intuitive mining of multilevel association, characterization and
classification rules. This framework is proposed as an extension of OLAP or an
alternative to Han's OLAM. OLAM processes data stored in data cubes structure of
which is based on a given conceptual hierarchy. OLAM SE determines minimum
support value from user defined cover of data with usage of entropy coding
principle. It also automatically determines the maximum threshold
to avoid explaining obvious. Major part of data is thus described by frequent
patterns. The presentation of results is inspired by UML diagram notation. It is
a graph nodes of which are frequent data sets represented as packages including
sub packages - data classes or items. Edges represent relations or patterns
between packages. These patterns can be interactively explored by the user, who
gets a detailed view of attractive ones. Other, possibly interesting, sets are
intuitively offered to her. This is well applicable for the characterization and
non-naive Bayesian classification.",
  address="VŠB-Technical University of Ostrava",
  booktitle="ZNALOSTI 2007, Proceedings of the 6th annual conference",
  chapter="28581",
  howpublished="print",
  institution="VŠB-Technical University of Ostrava",
  year="2007",
  month="february",
  pages="308--311",
  publisher="VŠB-Technical University of Ostrava",
  type="conference paper"
}