2010Advanced materials researchRequires access

Attribute Reduction Method of Uncertain Information

Xu E, Liang Shan Shao, Qiao Zhu, Guang Hui Cao, Feng Qiu

Open publisher page 0 citations

Abstract

To attribute reduction in an uncertain information system, this paper proposed a method of attribute reduction based on rough set theory. This reduction method gives the concepts of tolerance relationship, attribute significance and tolerance relationship similar matrix to deal with the inconsistency problem of in the information table. And then obtains the core attributes of incomplete information systems via the tolerance relationship similar matrix. Finally, according to attribute frequency in the tolerance relationship similar matrix, as the heuristic knowledge, makes use of binsearch heuristic algorithm to calculate the candidate attribute expansion so that it can reduce the expansion times to speed up reduction. Experiment results show that the algorithm is simple and effective.

About this research paper

What this paper is about

To attribute reduction in an uncertain information system, this paper proposed a method of attribute reduction based on rough set theory. This reduction method gives the concepts of tolerance relationship, attribute significance and tolerance relationship similar matrix to deal with the inconsistency problem of in the information table. And then obtains the core attributes of incomplete information systems via the tolerance relationship similar matrix. Finally, according to attribute frequency in the tolerance relationship similar matrix, as the heuristic knowledge, makes use of binsearch heuristic algorithm to calculate the candidate attribute expansion so that it can reduce the expansion times to speed up reduction. Experiment results show that the algorithm is simple and effective.

Why it matters

A significance statement is not available in the OpenAlex record.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

To attribute reduction in an uncertain information system, this paper proposed a method of attribute reduction based on rough set theory. This reduction method gives the concepts of tolerance relationship, attribute significance and tolerance relationship similar matrix to deal with the inconsistency problem of in the information table. And then obtains the core attributes of incomplete information systems via the tolerance relationship similar matrix. Finally, according to attribute frequency in the tolerance relationship similar matrix, as the heuristic knowledge, makes use of binsearch heuristic algorithm to calculate the candidate attribute expansion so that it can reduce the expansion times to speed up reduction. Experiment results show that the algorithm is simple and effective.

Key concepts: Rough set, Reduction (mathematics), Heuristic, Matrix (chemical analysis), Attribute domain, Set (abstract data type), Algorithm, Data mining

Related papers

Back to paper searchBrowse research topicsOriginal source
Attribute Reduction Method of Uncertain Information — Research Paper | ScholarLens