Improvement on agglomerative hierarchical clustering algorithm based on tree data structure with bidirectional approach

Hussain Abu Dalbouh, Norita Md Norwawi

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Scopus citations

Abstract

Hierarchical clustering algorithms take an input of pairwise data-item similarities and output a hierarchy of the data-items. This paper presents bidirectional agglomerative hierarchical clustering algorithm to create a bottom-up hierarchy, by iteratively merging the closest pair of data-items into one cluster. The result is a rooted AVL tree. The n leafs correspond to input data-items that need to n/2 or n/2+1 steps to merge into one cluster, correspond to groupings of items in coarser granularities climbing towards the root. As observed from the time complexity and number of steps needed to cluster all data points into one cluster perspective, the performance of the bidirectional agglomerative algorithm using tree data structure is better than the current agglomerative algorithms. Analysis on the experimental results indicates that the improved algorithm has a higher efficiency than previous methods.

Original languageEnglish
Title of host publicationProceedings - 3rd International Conference on Intelligent Systems Modelling and Simulation, ISMS 2012
Pages25-30
Number of pages6
DOIs
StatePublished - 2012
Externally publishedYes
Event3rd International Conference on Intelligent Systems Modelling and Simulation, ISMS 2012 - Kota Kinabalu, Malaysia
Duration: 8 Feb 201210 Feb 2012

Publication series

NameProceedings - 3rd International Conference on Intelligent Systems Modelling and Simulation, ISMS 2012

Conference

Conference3rd International Conference on Intelligent Systems Modelling and Simulation, ISMS 2012
Country/TerritoryMalaysia
CityKota Kinabalu
Period8/02/1210/02/12

Keywords

  • Bidirectional algorithm
  • Complexity
  • Hierarchical
  • Tree

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