Ant colony algorithm for text classification in multicore-multithread environment

This paper presents about Ant Colony Algorithm (ACO) for Text Classification in Multicore-Multithread Environment in Artificial Intelligent domain. We had develop a software which assimilate concurrency concept to multiple artificial ants. Pheromone in ACO is the main concept used to solve the text...

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Bibliographic Details
Published in:Indonesian Journal of Electrical Engineering and Computer Science Vol. 18; no. 3; p. 1359
Main Authors: Nazmi Fadzal, Ahmad, Puteh, Mazidah, Abd Rahman, Nurazzah
Format: Journal Article
Language:English
Published: 01.06.2020
ISSN:2502-4752, 2502-4760
Online Access:Get full text
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Summary:This paper presents about Ant Colony Algorithm (ACO) for Text Classification in Multicore-Multithread Environment in Artificial Intelligent domain. We had develop a software which assimilate concurrency concept to multiple artificial ants. Pheromone in ACO is the main concept used to solve the text classification problem. In regards to its role, pheromone value is changed depending on the solution finding that has been discovered at the pseudo random heuristic attempt in selecting path from text words. However, ACO can take up longer time to process larger training document. Based on the cooperative concept of ants living in colony, the ACO part is examined to work in multicore-multithread environment as to cater additional execution time benefit. In running multicore-multithread environment, the modification aims to make artificial ants actively communicate between multiple physical cores of processor. The execution time reduction is expected to show an improvement without compromising the original classification accuracy by the investment of trading on more processing power. The single and multicore-multithreaded version of ACO was compared statistically by conduction relevant test. It was found that the result shows a positive time reduction improvement.
ISSN:2502-4752
2502-4760
DOI:10.11591/ijeecs.v18.i3.pp1359-1366