Access Restriction

Author Weifeng Zhang ♦ Zengchang Qin
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©2011
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Special computer methods
Subject Keyword Pragmatics ♦ Clustering algorithms ♦ Semantics ♦ Image color analysis ♦ Silicon ♦ Algorithm design and analysis ♦ Humans ♦ Imprecise Concept Modeling ♦ Clustering ♦ Label Semantics ♦ Linguistic Expressions ♦ K-means
Abstract Cluster analysis is the assignment of grouping a set of observations into clusters so that observations in the same cluster are similar in some sense. One of the key features for clustering is how to define a sensible similarity measure. However, classical clustering algorithms have no ability to cluster data instances and imprecise concepts using traditional distance measures. In this paper, we proposed a (dis)similarity measure based on a new knowledge representation framework called label semantics. Based on this new measure, we can automatically cluster data instance and descriptive concepts represented by logical expressions of linguistic labels. Experimental results on a toy problem in image classification demonstrate the effectiveness of the new proposed clustering algorithm. Since the new proposed measure can be extended to measuring distance between any two granularities, the new clustering algorithms can also be extended to clustering data instance and imprecise concepts represented by other granularities.
Description Author affiliation: Intelligent Computing and Machine Learning Lab School of ASEE, Beihang University (Zengchang Qin) || Intelligent Computing and Machine Learning Lab, School of Automation Science and Electrical Engineering, Beihang University, China (Weifeng Zhang)
ISBN 9781424473151
ISSN 10987584
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2011-06-27
Publisher Place Taiwan
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
e-ISBN 9781424473175
Size (in Bytes) 583.64 kB
Page Count 6
Starting Page 603
Ending Page 608

Source: IEEE Xplore Digital Library