Tech Reports

Tech Report kmi-01-18 Abstract

Hierarchical clustering speed up using position lists and data position hierarchy
Techreport ID: kmi-01-18
Date: 2001
Author(s): Jiri Komzak

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

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With over a billion users, today's Internet is arguably the most successful human artifact ever created. The Internet's physical infrastructure, software, and content now play an integral part of the lives of everyone on the planet, whether they interact with it directly or not. Now nearing its fifth decade, the Internet has shown remarkable resilience and flexibility in the face of ever increasing numbers of users, data volume, and changing usage patterns, but faces growing challenges in meetings the needs of our knowledge society. Globally, many major initiatives are underway to address the need for more scientific research, physical infrastructure investment, better education, and better utilisation of the Internet. Within Japan, USA and Europe major new initiatives have begun in the area.

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