Particle Swarm Optimization for Punjabi Text Summarization

Particle swarm optimization (PSO) algorithm is proposed to deal with text summarization for the Punjabi language. PSO based on intelligence that predicts among a given set of solutions which best solution. The search carried out by extremely high-speed particles. It updates particle position and velocity at end iteration so during development generations, personal solution global are updated. Calculation within performed using fitness function looks into various statistical linguistic features datasets. Two datasets—monolingual corpus from Indian Languages Corpora Initiative Phase-II Punjabi-Hindi parallel corpus—are considered. comprises 1,000 sentences tourism domain while monolingual contains 30,000 general domain. ROUGE measures evaluate summary where highest measure, ROUGE-1, achieved precision, recall, F-measure as 0.7836, 0.7957, 0.7896, respectively.