Detail publikace

Association Based Classification for Relational Data and Its Use in Web Mining

BARTÍK, V.

Originální název

Association Based Classification for Relational Data and Its Use in Web Mining

Anglický název

Association Based Classification for Relational Data and Its Use in Web Mining

Jazyk

en

Originální abstrakt

Classification based on mining association rules is a method with good accuracy and human readable classification model. The aim of this paper is to propose modification of the basic association based classification method, which can be used for the data extracted from web pages. In this paper, the modifications of the method and necessary discretization of numeric attributes will be described. Next, the experiments with various data will be presented, with emphasis on data obtained by extraction and segmentation of web pages.

Anglický abstrakt

Classification based on mining association rules is a method with good accuracy and human readable classification model. The aim of this paper is to propose modification of the basic association based classification method, which can be used for the data extracted from web pages. In this paper, the modifications of the method and necessary discretization of numeric attributes will be described. Next, the experiments with various data will be presented, with emphasis on data obtained by extraction and segmentation of web pages.

Dokumenty

BibTex


@inproceedings{BUT30203,
  author="Vladimír {Bartík}",
  title="Association Based Classification for Relational Data and Its Use in Web Mining",
  annote="Classification based on mining association rules is a method with good accuracy
and human readable classification model. The aim of this paper is to propose
modification of the basic association based classification method, which can be
used for the data extracted from web pages. In this paper, the modifications of
the method and necessary discretization of numeric attributes will be described.
Next, the experiments with various data will be presented, with emphasis on data
obtained by extraction and segmentation of web pages.",
  address="IEEE Computer Society",
  booktitle="2009 IEEE Symposium on Computational Intelligence and Data Mining Proceedings",
  chapter="30203",
  edition="NEUVEDEN",
  howpublished="print",
  institution="IEEE Computer Society",
  year="2009",
  month="april",
  pages="252--258",
  publisher="IEEE Computer Society",
  type="conference paper"
}