# Compressing sparse tries using multidimensional matrices [closed]

Wikipedia's trie article says:

[Compressing the trie representation by merging the common branches] is also typically used in the implementation of the various fast lookup tables needed to retrieve Unicode character properties (for example to represent case mapping tables, or lookup tables containing the combination of base and combining characters needed to support Unicode normalization). For such application, the representation is similar to transforming a very large unidimensional sparse table into a multidimensional matrix, and then using the coordinates in the hyper-matrix as the string key of an uncompressed trie. The compression will then consist of detecting and merging the common columns within the hyper-matrix to compress the last dimension in the key; each dimension of the hypermatrix stores the start position within a storage vector of the next dimension for each coordinate value, and the resulting vector is itself compressible when it is also sparse, so each dimension (associated to a layer level in the trie) is compressed separately.

This is all uncited! It says it is similar to "transforming a very large unidimensional sparse table into a multidimensional matrix". What is such a transformation, and how such a matrix is helpful to implementing a compressed trie? I've been unable to find anything. Obviously, not understanding this, I'm at a loss for how using the coordinates within that allow one to implement a trie!

• This does not appear to be a question. – Ellen Spertus Feb 3 '15 at 0:27
• @espertus Does that edit make the question sufficiently obvious? – gsnedders Feb 3 '15 at 0:30
• I'd suggest rewriting your question, starting with a narrow question, such as: "How is a X transformed into a Y, and why would one do so?" You can then say you checked the Wikipedia article but don't understand detail Z about it. – Ellen Spertus Feb 3 '15 at 0:33