Knowledge discovery in data using formal concept analysis and random projections

Cherukuri Aswani Kumar

International Journal of Applied Mathematics and Computer Science (2011)

  • Volume: 21, Issue: 4, page 745-756
  • ISSN: 1641-876X

Abstract

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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.

How to cite

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Cherukuri Aswani Kumar. "Knowledge discovery in data using formal concept analysis and random projections." International Journal of Applied Mathematics and Computer Science 21.4 (2011): 745-756. <http://eudml.org/doc/208085>.

@article{CherukuriAswaniKumar2011,
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.},
author = {Cherukuri Aswani Kumar},
journal = {International Journal of Applied Mathematics and Computer Science},
keywords = {attribute implications; concept lattices; dimensionality reduction; formal concept analysis; knowledge discovery; random projections},
language = {eng},
number = {4},
pages = {745-756},
title = {Knowledge discovery in data using formal concept analysis and random projections},
url = {http://eudml.org/doc/208085},
volume = {21},
year = {2011},
}

TY - JOUR
AU - Cherukuri Aswani Kumar
TI - Knowledge discovery in data using formal concept analysis and random projections
JO - International Journal of Applied Mathematics and Computer Science
PY - 2011
VL - 21
IS - 4
SP - 745
EP - 756
AB - 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.
LA - eng
KW - attribute implications; concept lattices; dimensionality reduction; formal concept analysis; knowledge discovery; random projections
UR - http://eudml.org/doc/208085
ER -

References

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