Tech Report

Hierarchical clustering speed up using position lists and data position hierarchy

The aim of this paper is to address the nature of hierarchical clustering problems in systems with very large numbers of entities, and to propose specific speed improvements in the clustering algorithm. The motivation for this theme arises from the challenge of visualising the geographic and logical distribution of many tens of thousands of distance-learning students at the UK's Open University. A general algorithm for solving hierarchical clustering is mentioned at the beginning. Then the paper describes (i) a speed-up technique based on lists sorted according to particular dimensions or attributes of the entities to be visualised and (ii) a speed-up technique based upon hierarchical partitioning into regions. At the end, the paper discusses the algorithm's complexity and presents experimental results.

Keywords

hierarchical clustering, position hierarchy, position list, geographical information system

ID: kmi-01-18

Date: 2001

Author(s): Jiri Komzak

Resources:
Download PDF

View By

Other Publications

Latest Seminar
Dr Joseph Kwarteng
Knowledge Media Institute, The Open University

Understanding Misogynoir Online: Challenges in Identifying Intersectional Hate Speech

Watch the live webcast

CONTACT US

Knowledge Media Institute
The Open University
Walton Hall
Milton Keynes
MK7 6AA
United Kingdom

Tel: +44 (0)1908 653800

Fax: +44 (0)1908 653169

Email: KMi Support

COMMENT

If you have any comments, suggestions or general feedback regarding our website, please email us at the address below.

Email: KMi Development Team