Storage optimization of tree structured files representing descriptor sets

Rotwitt, Theodore; DeMaine, P. A. D.

doi:10.1145/1734714.1734730

Cited by 11 publications

(4 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…If the principle of commonality is not obeyed, then the amount of storage required for the abstract network can increase dramatically. However, the speed of retrieval is not measurably affected [24]. It should be recalled that the security facility can always be invoked to deny unauthorized access to any item of information.…”

Section: Tql Examplesmentioning

confidence: 99%

“…However, because only non-redundant information is inserted into RFILE, the number of information paths stored per memory block significantly increase when the number of entries in a database(s) increases [24]. We have estimated that less than one eighth of the storage that is required to store the formulae in the National Compound Registry, which has more than 8,000,000 entries, is required for RFILE.…”

Section: B Expected Performancementioning

confidence: 99%

See 1 more Smart Citation

High-speed tools for Global Information Management I. Information processing and retrieval

Maine

Bradley

1996

Journal of Systems Integration

View full text Add to dashboard Cite

Abstract. The general specifications and design for a High-Speed General Information Management System, HSGIMS, to serve as the basis for a Global Information Network are given. Some of the key specifications that have been confirmed in experiments with a prototype of the HSG1MS are:(1) Information (or data) and Question-type (or logical data) independence.(2) Very small bounded search times that are independent of the amount of information that is managed and can be computed exactly.(3) A fool-proof security system that can be used to protect databases against viruses and can also be easily invoked to deny unauthorized access by users.(4) Efficient use of all storage and communications resources.

show abstract

Section: Tql Examplesmentioning

confidence: 99%

Section: B Expected Performancementioning

confidence: 99%

High-speed tools for Global Information Management I. Information processing and retrieval

Maine

Bradley

1996

Journal of Systems Integration

View full text Add to dashboard Cite

show abstract

“…De Maine and Rotwitt 5 found that the order in which the characters are tested in building the trie has influences on the size of resulting tries. Using this idea, Comer and Sethi 6 defined the ordercontaining trie (O-Trie).…”

Section: Introductionmentioning

confidence: 99%

A new heuristic for full trie minimization

Zhang¹,

Chen²,

Zhang³

et al. 2019

ScienceAsia

View full text Add to dashboard Cite

Trie is a data structure with many applications. High space usage is the major drawback of the trie. The order-containing trie optimizes the space usage of the trie by rearranging symbols of strings. We present a new heuristic for building order-containing tries with small space. The heuristic is based on the following observation. For a given string set P, by moving the symbols on a position to the first position of strings in P, the trie of the resulting pattern set may have fewer nodes than that of the trie of P. We present an algorithm to find positions that yield the smallest such trie. The algorithm runs in O(P) time and uses O(|P| log|P|) bits space, where P is the number of total symbols in P, and |P| is the number of patterns in P. By using this method recursively in trie constructions, we can build a trie with fewer nodes than the trie of P. We conduct several experiments that show the new heuristic builds smaller tires than previous work.

show abstract

“…For details see [lOI. As noted in [3,12] and [4], the high space requirement is the main disadvantage of tries, so in this paper we present several algorithms for reducing the space while trying to preserve the efficiency of the trie search. As first observed by Rotwitt and de Maine [13], one way to reduce the number of nodes of a trie, and thus to reduce the total space required, is to reorder the testing of attributes. As a trivial example of this approach, consider the trie representation for the words WITH, WITS, WIFE.…”

Section: An Introduction To the Trie Data Structurementioning

confidence: 99%

Algorithms for trie compaction

Alsuwaiyel

Horowitz

1984

ACM Trans. Database Syst.

View full text Add to dashboard Cite

The trie data structure has many properties which make it especially attractive for representing large files of data. These properties include fast retrieval time, quick unsuccessful search determination, and finding the longest match to a given identifier. The main drawback is the space requirement. In this paper the concept of trie compaction is formalized. An exact algorithm for optimal trie compaction and three algorithms for approximate trie compaction are given, and an analysis of the three algorithms is done. The analyses indicate that for actual tries, reductions of around 70 percent in the space required by the uncompacted trie can be expected. The quality of the compaction is shown to be insensitive to the number of nodes, while a more relevant parameter is the alphabet size of the key.

show abstract

Storage optimization of tree structured files representing descriptor sets

Cited by 11 publications

References 4 publications

High-speed tools for Global Information Management I. Information processing and retrieval

High-speed tools for Global Information Management I. Information processing and retrieval

A new heuristic for full trie minimization

Algorithms for trie compaction

Contact Info

Product

Resources

About