Construction of FuzzyFind Dictionary using Golay Coding Transformation for Searching Applications

TL;DR

This paper introduces a novel FuzzyFind Dictionary construction method using Golay Coding Transformation for efficient large-scale data searching, achieving linear time generation and constant time access.

Contribution

It presents a new technique combining Golay Coding with FuzzyFind Dictionary for fast, scalable text search in big data, with efficient updates and high accuracy.

Findings

Linear time complexity for dictionary generation

Constant time complexity for data access and updates

Effective handling of large datasets with high accuracy

Abstract

Searching through a large volume of data is very critical for companies, scientists, and searching engines applications due to time complexity and memory complexity. In this paper, a new technique of generating FuzzyFind Dictionary for text mining was introduced. We simply mapped the 23 bits of the English alphabet into a FuzzyFind Dictionary or more than 23 bits by using more FuzzyFind Dictionary, and reflecting the presence or absence of particular letters. This representation preserves closeness of word distortions in terms of closeness of the created binary vectors within Hamming distance of 2 deviations. This paper talks about the Golay Coding Transformation Hash Table and how it can be used on a FuzzyFind Dictionary as a new technology for using in searching through big data. This method is introduced by linear time complexity for generating the dictionary and constant time complexity to access the data and update by new data sets, also updating for new data sets is linear time depends on new data points. This technique is based on searching only for letters of English that each segment has 23 bits, and also we have more than 23-bit and also it could work with more segments as reference table.