Well... it makes it uncomputable in explicit form. Sometimes there are implicit forms for the matrix that keeps the size in bounds. For instance, limited rank decompositions (aka truncated singular value decompositions) can be represented by storing two skinny matrices and a diagonal that don't take much more memory/disk than the original data.
On Mon, Jul 18, 2011 at 12:17 AM, Sebastian Schelter (JIRA) <[email protected] > wrote: > The problem with this naive approach is that the resulting matrix is going > to be huge (millions of users times hundred thousands of items) and dense, > which makes it uncomputable.
