Complete inverted files for efficient text retrieval and analysis
Journal of the ACM (JACM)
Implementing dynamic minimal-prefix tries
Software—Practice & Experience
The Unicode standard, version 2.0
The Unicode standard, version 2.0
The art of computer programming, volume 3: (2nd ed.) sorting and searching
The art of computer programming, volume 3: (2nd ed.) sorting and searching
ACM Computing Surveys (CSUR)
Communications of the ACM
Communications of the ACM
Efficient string matching: an aid to bibliographic search
Communications of the ACM
Communications of the ACM
Data Structures and Algorithms
Data Structures and Algorithms
Tries for Approximate String Matching
IEEE Transactions on Knowledge and Data Engineering
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In this paper, we explore 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: \Sigma^* \rightarrow (\sigma^q)^*. 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.