Storing a Sparse Table with 0(1) Worst Case Access Time
Journal of the ACM (JACM)
A polynomial time generator for minimal perfect hash functions
Communications of the ACM
Finding minimal perfect hash functions
SIGCSE '86 Proceedings of the seventeenth SIGCSE technical symposium on Computer science education
Collections of functions for perfect hashing
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Perfect hashing for external files
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File organization and processing
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Information Systems
A more cost effective algorithm for finding perfect hash functions
CSC '89 Proceedings of the 17th conference on ACM Annual Computer Science Conference
Perfect hashing using sparse matrix packing
Information Systems
Near—perfect hashing of large word sets
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Practical minimal perfect hash functions for large databases
Communications of the ACM
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The study of an ordered minimal perfect hashing scheme
Communications of the ACM
File organization: implementation of a method guaranteeing retrieval in one access
Communications of the ACM
Reciprocal hashing: a method for generating minimal perfect hashing functions
Communications of the ACM
Minimal perfect hash functions made simple
Communications of the ACM
Communications of the ACM
Perfect hashing functions: a single probe retrieving method for static sets
Communications of the ACM
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Handling identifies as internal symbols in language processors
Communications of the ACM
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Finding Minimal Perfect Hash Functions
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Reducing the Storage Requirements of a Perfect Hash Function
IEEE Transactions on Knowledge and Data Engineering
A compact static double-array keeping character codes
Information Processing and Management: an International Journal
Implementation of dictionaries via automata and decision trees
CIAA'02 Proceedings of the 7th international conference on Implementation and application of automata
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Many current perfect hashing algorithms suffer from the problem of pattern collisions. In this paper, a perfect hashing technique that uses array-based tries and a simple sparse matrix packing algorithm is introduced. This technique eliminates all pattern collisions, and, because of this, it can be used to form ordered minimal perfect hashing functions on extremely large word lists. This algorithm is superior to other known perfect hashing functions for large word lists in terms of function building efficiency, pattern collision avoidance, and retrieval function complexity. It has been successfully used to form an ordered minimal perfect hashing function for the entire 24481 element Unix word list without resorting to segmentation. The item lists addressed by the perfect hashing function formed can be ordered in any manner, including alphabetically, to easily allow other forms of access to the same list.