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Permanent link (DOI): https://doi.org/10.7939/R35Q4RX5S

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Efficient Algorithms for Hierarchical Agglomerative Clustering Open Access

Descriptions

Other title
NA
Subject/Keyword
Hierarchical Agglomerative Clustering
Cover tree
Type of item
Thesis
Degree grantor
University of Alberta
Author or creator
Anandan, Ajay
Supervisor and department
Barbosa,Denilson (Department of Computing Science)
Examining committee member and department
Lu, Paul (Department of Computing Science)
Sander, Joerg (Department of Computing Science)
Department
Department of Computing Science
Specialization

Date accepted
2013-08-28T11:55:54Z
Graduation date
2013-11
Degree
Master of Science
Degree level
Master's
Abstract
This thesis proposes and evaluates methods to improve two algorithmic ap- proaches for Hierarchical Agglomerative Clustering. These new methods in- crease the scalability and speed of the traditional Hierarchical Agglomerative Clustering algorithm without using any approximations. The first method exploits the characteristics of modern Non-Uniform Memory Access architec- tures, resulting in a parallel algorithm for the stored matrix version of Hier- archical Agglomerative Clustering. The second method uses a data structure called the Cover Tree to speed up the stored data version of the Hierarchical Agglomerative Clustering. For the second method, the thesis proposes both se- quential and parallel algorithms. All methods were experimentally evaluated and compared against the state-of-the-art approaches for high performance clustering. The results demonstrate the superiority of the parallel approaches with respect to all baselines and previous work, and the comparison between the stored matrix and the stored
Language
English
DOI
doi:10.7939/R35Q4RX5S
Rights
Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of these terms. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.
Citation for previous publication
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