Creator:

Aswani Kumar, Cherukuri

Contributor:

Korbicz, Józef - red. ; Uciński, Dariusz - red.

Title:

Knowledge discovery in data using formal concept analysis and random projections

Group publication title:

AMCS, Volume 21 (2011)

Subject and Keywords:

attribute implications ; concept lattices ; dimensionality reduction ; formal concept analysis ; knowledge discovery ; random projections

Abstract:

In this paper our objective is to propose a random projections based formal concept analysis for knowledge discovery in data. We demonstrate the implementation of the proposed method on two real world healthcare datasets. Formal Concept Analysis (FCA) is a mathematical framework that offers a conceptual knowledge representation through hierarchical conceptual structures called concept lattices. However, during the design of a concept lattice, complexity plays a major role.

Publisher:

Zielona Góra: Uniwersytet Zielonogórski

Date:

2011

Resource Type:

artykuł

DOI:

10.2478/v10006-011-0059-1

Pages:

745-756

Source:

AMCS, Volume 21, Number 4 (2011) ; click here to follow the link

Language:

eng

Rights:

Biblioteka Uniwersytetu Zielonogórskiego