base for example if a pair of media items say the song u201c uptown girl u201d by billy joel and u201c hallelujah u201d by jeff buckley appear together in 42 different mediasets in the knowledge base not necessarily adjacent one another then the co concurrency metric might be 42 or some other figure depending on the scaling selected normalization etc in some embodiments this figure or co concurrency u201c weight u201d may be normalized to a number between zero and one referring now to fig1 a matrix 100 illustrates a useful method for storing the metric values or weights for any particular metric here individual media items in the knowledge base say m 1 m 2 m 3 m k are assigned corresponding rows and columns in the matrix in the matrix the selected metric weight for every pair of items is entered at row column location x y corresponding to the two media items defining the pair in fig1 a the values are normalized now we assume an input set of media items is received referring again to process step 302 a collection of u201c candidate media items u201d most similar to the input media items is generated based on a metric matrix like matrix 100 of fig1 a for instance for each media item say item m 2 in the input set 301 process 302 could add to a.