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Remainder Quotient Double Hashing Technique in Closed Hashing Search Process

Authors: STUTI PANDEY; Abhay Kumar Agarwal;

Remainder Quotient Double Hashing Technique in Closed Hashing Search Process

Abstract

Searching is one of the most important process in many activities to access the data or elements. It can be done both in online and offline mode. Many algorithms are used in data structure to perform search process. Hash search algorithm is one of them which are independent of the number of elements inserted into the table. The aim of this research paper is to study about double hashing method of hash search algorithm for minimizing the collisions during insertion and searching of elements into a table. The results of this research reveal the fact that the searching through double hashing method performs efficient and quicker searching among all other existing searching methods. All these analysis gives an idea to search the elements into two tables i.e main table and collision table. By dividing the elements into two tables, the searching method is anticipated to be quicker than the elements accumulated in one table as well as collisions can also be avoided.

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selected citations
These citations are derived from selected sources.
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).
BIP!Citations provided by BIP!
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.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
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