# Knowledge discovery in data using formal concept analysis and random projections

International Journal of Applied Mathematics and Computer Science (2011)

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

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topCherukuri 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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