Linear Time Baire Hierarchical Clustering for Enterprise Information Retrieval
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Pedro Contreras,Fionn Murtagh. Linear Time Baire Hierarchical Clustering for Enterprise Information Retrieval. International Journal of Software and Informatics, 2012,6(3):363~380
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Abstract:The Baire or longest common prefix metric induces an ultrametric or tree topology. It has many interesting properties such as the following: the Baire distance, or metric, is also an ultrametric; associated with the tree topology is a hierarchically-structured, embedded set of clusters; the hierarchical clustering can be viewed in terms of density-based and grid-based structuring of the data. We are interested in using the hierarchical structuring of the data induced by the Baire metric for top-down search, in an information retrieval context. Enterprise search and retrieval requires exhaustivity of retrievals. Another requirement is that enterprise search supports situation awareness in order to implement different policies of access to, and use of, data. We show how situation awareness can be supported by the Baire metric, as used for structuring data in order to support enterprise search and retrieval.
keywords:information retrieval  search  exact match  partial match  best match  query  enterprise  metric  ultrametric  hierarchy  tree  longest common prefix  computation  effciency  linear time  logarithmic time
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