Knowledge discovery in data using formal concept analysis and random projections

Author:

Kumar Cherukuri

Abstract

Knowledge discovery in data using formal concept analysis and random projections 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

Walter de Gruyter GmbH

Subject

Applied Mathematics,Engineering (miscellaneous),Computer Science (miscellaneous)

Reference32 articles.

1. Database friendly random projections: Johnson-Lindenstrauss with binary coins;D. Achilioptas;Journal of Computer and System Sciences,2003

2. Analysis of unsupervised dimensionality reductions;Ch. Aswani Kumar;Computer Science and Information Systems,2009

3. Random projections for concept lattice reduction;Aswani Kumar,2010

4. Reducing data dimensionality using random projections and fuzzy k-means clustering;Aswani Kumar;International Journal of Intelligent Computing and Cybernetics,2011

5. Latent semantic indexing using eigenvalue analysis for efficient information retrieval;S. Aswani Kumar;International Journal of Applied Mathematics and Computer Science,2006

Cited by 47 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Influence of Attribute Granulation on Three-Way Concept Lattices;Big Data Mining and Analytics;2024-09

2. Non-redundant implicational base of formal context with constraints using SAT;PeerJ Computer Science;2024-01-31

3. Attribute granulation in fuzzy formal contexts based on L-fuzzy concepts;International Journal of Approximate Reasoning;2023-08

4. Factorizing lattices by interval relations;International Journal of Approximate Reasoning;2023-06

5. Multilevel Conflict Analysis Based on Fuzzy Formal Contexts;IEEE Transactions on Fuzzy Systems;2022-12

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3