By Topic

Analysis and Representation of Biomedical data with Concept Lattice

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Huaiguo Fu ; Telecommunications Software & Systems Group, Waterford Institute of Technology, Waterford, Ireland. email: hfu@tssg.org ; Brendan Jennings ; Paul Malone

As the progress in biology and medical science, especially in DNA technology, large amounts of biomedical data continue to grow inexorably in size, dimension and complexity. We need to develop more scalable and more efficient techniques and methods to analyze and represent the large and high-dimensional biomedical data sets. Formal concept analysis (FCA) is an effective tool for data analysis and knowledge discovery. Concept lattice, which is derived from mathematical order theory and lattice theory, is the core of FCA. Many research works of various areas show that concept lattice structure is an effective platform for data mining, machine learning, information retrieval, software engineering, etc. This paper presents FCA for analysis and representation of biomedical data. Furthermore, we present a new lattice-based algorithm for analysis of large and high-dimensional biomedical data.

Published in:

2007 Inaugural IEEE-IES Digital EcoSystems and Technologies Conference

Date of Conference:

21-23 Feb. 2007