Title :
Time-space trade-off analysis of morphic trie images
Author_Institution :
Dept. of Comput., Hong Kong Polytech. Univ., Hung Hom, China
Abstract :
The author explores the use of tries to represent tries. A morphic trie image is a trie that represents a set of transformed keywords using an isomorphism h:Σ*→(σq)*. Morphic trie images using tenary alphabets achieve near optimal performances but approximation errors degrade their performances. A condition which determines whether tenary or bit tries should be used is found. Even though bit tries have better storage reduction in some cases, tenary tries access faster than bit tries. We show that the morphic trie images use less space than minimal prefix tries. If morphic trie images were compressed to form minimal prefix tries, then the total storage reduction is the product of the two. Approximation errors have no effect on minimal prefix tries
Keywords :
data compression; image coding; spatial data structures; tree data structures; tree searching; trees (mathematics); approximation errors; bit tries; image compression; isomorphism; key retrieval algorithm; minimal prefix tries; morphic trie images; near optimal performances; storage reduction; ternary alphabets; ternary tries; time-space trade-off analysis; transformed keywords; trie hashing; Approximation error; Database systems; Degradation; Dictionaries; Image analysis; Image coding; Image storage; Information retrieval; Testing; Tree data structures;
Journal_Title :
Knowledge and Data Engineering, IEEE Transactions on