1. A method for generating a parsimonious multi-resolution representation of value-item lists, the method comprising: receiving a set of values for a set of measure attributes and a set of values for a set of dimension attributes; inferring an initial hierarchic data structure based at least in part on count data associated with the received set of values for dimension attributes; distributing the received set of values for the set of measure attributes into a set of value-item lists associated with a portion of leaf nodes in the hierarchic data structure; in the hierarchic data structure recursively rearranging from bottom to top the set of value-item lists associated with the portion of leaf nodes based at least in part on compression performance stemming from the rearrangement of the set of value-item lists; reducing a number of features in the set of measure attributes, prior to the recursive rearrangement of the set of value-item lists; and promoting a plurality of value-item elements from the rearranged lists into a tree structure to generate a parsimonious representation of the inferred hierarchic data structure.
1. A method for generating a parsimonious multi-resolution representation of value-item lists, the method comprising: receiving a set of values for a set of measure attributes and a set of values for a set of dimension attributes; inferring an initial hierarchic data structure based at least in part on count data associated with the received set of values for dimension attributes; distributing the received set of values for the set of measure attributes into a set of value-item lists associated with a portion of leaf nodes in the hierarchic data structure; in the hierarchic data structure recursively rearranging from bottom to top the set of value-item lists associated with the portion of leaf nodes based at least in part on compression performance stemming from the rearrangement of the set of value-item lists; reducing a number of features in the set of measure attributes, prior to the recursive rearrangement of the set of value-item lists; and promoting a plurality of value-item elements from the rearranged lists into a tree structure to generate a parsimonious representation of the inferred hierarchic data structure. 12. The method of claim 1 , wherein the feature reduction is a Poisson decomposition.