K-tree : a height balanced tree structured vector quantizer
Geva, Shlomo (2000) K-tree : a height balanced tree structured vector quantizer. In NNSP-2000, IEEE Neural Network for Signal Processing Workshop 2000, 11-13 December 2000, Sydney.
We describe a clustering algorithm for the design of height balanced trees for vector quantisation. The algorithm is a hybrid of the B-tree and the k-means clustering procedure. K-tree supports on-line dynamic tree construction. The properties of the resulting search tree and clustering codebook are comparable to that of codebooks obtained by TSVQ, the commonly used recursive k-means algorithm for constructing vector quantization search trees. The K-tree algorithm scales up to larger data sets than TSVQ, produces codebooks with somewhat higher distortion rates, but facilitates greater control over the properties of the resulting codebooks. We demonstrate the properties and performance of K-tree and compare it with TSVQ and with k-means.
Impact and interest:
Citation counts are sourced monthly from and citation databases.
These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.
Citations counts from theindexing service can be viewed at the linked Google Scholar™ search.
Full-text downloads displays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.
|Item Type:||Conference Item (Other)|
|Additional Information:||Author selected Creative Commons Attributes on the license field|
|Keywords:||clustering, tree, hierarchical clustering, k-means, c-means|
|Subjects:||Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100)|
|Divisions:||Past > QUT Faculties & Divisions > Faculty of Science and Technology
Past > Schools > School of Software Engineering & Data Communications
|Copyright Owner:||Copyright 2000 IEEE|
|Copyright Statement:||Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.|
|Deposited On:||16 Dec 2008 22:34|
|Last Modified:||13 Jul 2011 22:19|
Available Versions of this Item
- K-tree : a height balanced tree structured vector quantizer. (deposited 16 Dec 2008 22:34) [Currently Displayed]
Repository Staff Only: item control page