Automatic Text Summarization for Hindi Using Real Coded Genetic Algorithm

In the present scenario, Automatic Text Summarization (ATS) is in great demand to address ever-growing volume of text data available online discover relevant information faster. this research, ATS methodology proposed for Hindi language using Real Coded Genetic Algorithm (RCGA) over health corpus, Kaggle dataset. The comprises five phases: preprocessing, feature extraction, processing, sentence ranking, and summary generation. Rigorous experimentation on varied sets performed where distinguishing features, namely- similarity named entity features are combined with others computing evaluation metrics. top 14 combinations evaluated through Recall-Oriented Understudy Gisting Evaluation (ROUGE) measure. RCGA computes appropriate weights strings chromosomes selection, reproduction operators: Simulating Binary Crossover Polynomial Mutation. To extract highest scored sentences as corpus summary, different compression rates tested. comparison existing summarization tools, extractive method gives a reduction 65%.