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Related Experiment Video

Updated: Feb 7, 2026

Pattern-based Search of Epigenomic Data Using GeNemo

Pattern-based Search of Epigenomic Data Using GeNemo

Published on: October 8, 2017

A new split based searching for exact pattern matching for natural texts.

Saqib Hakak¹, Amirrudin Kamsin¹, Palaiahnakote Shivakumara¹

¹Faculty of Computer Science and Information Technology, University of Malaya, Kuala Lumpur.

|July 27, 2018

Summary

This study introduces a novel exact pattern matching algorithm that splits query strings to improve both speed and memory efficiency. The new method enhances performance, especially for longer query patterns, across various text databases.

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Area of Science:

Computer Science
Algorithm Analysis

Background:

Exact pattern matching is crucial for diverse applications like bioinformatics and search engines.
Existing algorithms prioritize speed over memory efficiency.

Purpose of the Study:

To develop an exact pattern matching algorithm optimizing both time and memory consumption.
To introduce a novel string-splitting approach for enhanced search performance.

Main Methods:

The proposed algorithm divides the query pattern into two equal halves.
It searches for the second (right) half in the corpus and uses brute force for the remainder.
The algorithm was tested on multilingual text databases (Arabic, English, Chinese, Italian, French).

Main Results:

The novel algorithm demonstrates superior time efficiency compared to the existing S1 Algorithm.
Significant improvements in memory consumption were observed with increasing query pattern length.
Performance gains were consistent across various datasets.

Conclusions:

The proposed string-splitting exact pattern matching algorithm effectively balances time and memory efficiency.
This approach offers a viable alternative for applications requiring optimized pattern searching.
The algorithm's effectiveness is particularly pronounced for longer query patterns.