A pivot-based routine for improved parent-finding in hybrid MDS

Morrison, A. and Chalmers, M. (2004) A pivot-based routine for improved parent-finding in hybrid MDS. Information Visualization, 3(2), pp. 109-122. (doi: 10.1057/palgrave.ivs.9500069)

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The problem of exploring or visualising data of high dimensionality is central to many tools for information visualisation. Through representing a data set in terms of inter-object proximities, multidimensional scaling may be employed to generate a configuration of objects in low-dimensional space in such a way as to preserve high-dimensional relationships. An algorithm is presented here for a heuristic hybrid model for the generation of such configurations. Building on a model introduced in 2002, the algorithm functions by means of sampling, spring model and interpolation phases. The most computationally complex stage of the original algorithm involved the execution of a series of nearest-neighbour searches. In this paper, we describe how the complexity of this phase has been reduced by treating all high-dimensional relationships as a set of discretised distances to a constant number of randomly selected items: pivots. In improving this computational bottle-neck, the algorithmic complexity is reduced from O(N√N) to O(N5/4). As well as documenting this improvement, the paper describes evaluation with a data set of 108,000 13-dimensional items and a set of 23,141 17-dimensional items. Results illustrate that the reduction in complexity is reflected in significantly improved run times and that no negative impact is made upon the quality of layout produced.

Item Type:Articles
Glasgow Author(s) Enlighten ID:Morrison, Dr Alistair and Chalmers, Professor Matthew
Authors: Morrison, A., and Chalmers, M.
College/School:College of Science and Engineering > School of Computing Science
Journal Name:Information Visualization
ISSN (Online):1473-8724

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