We describe many vantage points on the Baire metric and its use in clustering data, or its use in preprocessing and structuring data in order to support search and retrieval operations. In some cases, we proceed directly to clusters and do not directly determine the distances. We show how a hierarchical clustering can be read directly from one pass through the data. We offer insights also on practical implications of precision of datameasurement. As a mechanism for treating multidimensional data, including very high dimensional data, we use random projections.
|Number of pages
|P-Adic Numbers, Ultrametric Analysis, and Applications
|Published - 1 Jan 2012