Part-of-Speech Tagging for Arabic Text using Particle Swarm Optimization and Genetic Algorithm

What is it about?

In this study, we propose a supervised POS tagging system for the Arabic language using Particle Swarm Optimization (PSO) and Genetic Algorithms (GA) as well as Hidden Markov Model (HMM). The tagging process is considered as an optimization problem and illustrated as a swarm, which consists of a group of particles. Each particle represents a sequence of tags. The PSO algorithm is applied to find the best sequence of tags, which represent the correct tags of the sentence. The genetic operators: crossover and mutation are used to find personal best, global best, and velocity of the PSO algorithm. HMM is used to find fitness of the particles in the swarm.

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Photo by Ayesha Firdaus on Unsplash

Photo by Ayesha Firdaus on Unsplash