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A refinement of hashing which allows retrieval of an item in a static table with a single probe is considered. Given a set I of identifiers, two methods are presented for building, in a mechanical way, perfect hashing functions, i.e. functions transforming the elements of I into unique addresses. The first method, the “quotient reduction” method, is shown to be complete in the sense that for every set I the smallest table in which the elements of I can be stored and from which they can be retrieved by using a perfect hashing function constructed by this method can be found. However, for nonuniformly distributed sets, this method can give rather sparse tables. The second method, the “remainder reduction” method, is not complete in the above sense, but it seems to give minimal (or almost minimal) tables for every kind of set. The two techniques are applicable directly to small sets. Some methods to extend these results to larger sets are also presented. A rough comparison with ordinary hashing is given which shows that this method can be used conveniently in several practical applications.
Information storage and retrieval of data, General topics in the theory of software, Algorithms in computer science
Information storage and retrieval of data, General topics in the theory of software, Algorithms in computer science
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 119 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 0.1% | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |