Automatic Text Summarization for Hindi Using Real Coded Genetic Algorithm
In the present scenario, Automatic Text Summarization (ATS) is in great demand to address the ever‐growing volume of text data available online to discover relevant information faster. In this research, the ATS methodology is proposed for the Hindi language using Real Coded Genetic Algorithm (RCGA)...
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Format: | Article |
Language: | English |
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MDPI
2022
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Online Access: | View Fulltext in Publisher |
LEADER | 02153nam a2200289Ia 4500 | ||
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001 | 10.3390-app12136584 | ||
008 | 220718s2022 CNT 000 0 und d | ||
020 | |a 20763417 (ISSN) | ||
245 | 1 | 0 | |a Automatic Text Summarization for Hindi Using Real Coded Genetic Algorithm |
260 | 0 | |b MDPI |c 2022 | |
856 | |z View Fulltext in Publisher |u https://doi.org/10.3390/app12136584 | ||
520 | 3 | |a In the present scenario, Automatic Text Summarization (ATS) is in great demand to address the ever‐growing volume of text data available online to discover relevant information faster. In this research, the ATS methodology is proposed for the Hindi language using Real Coded Genetic Algorithm (RCGA) over the health corpus, available in the Kaggle dataset. The methodology comprises five phases: preprocessing, feature extraction, processing, sentence ranking, and summary generation. Rigorous experimentation on varied feature sets is performed where distinguishing features, namely‐ sentence similarity and named entity features are combined with others for computing the evaluation metrics. The top 14 feature combinations are evaluated through Recall‐Oriented Understudy for Gisting Evaluation (ROUGE) measure. RCGA computes appropriate feature weights through strings of features, chromosomes selection, and reproduction operators: Simulating Binary Crossover and Polynomial Mutation. To extract the highest scored sentences as the corpus summary, different compression rates are tested. In comparison with existing summarization tools, the ATS extractive method gives a summary reduction of 65%. © 2022 by the authors. Licensee MDPI, Basel, Switzerland. | |
650 | 0 | 4 | |a automatic text summarization |
650 | 0 | 4 | |a extractive summary |
650 | 0 | 4 | |a feature set |
650 | 0 | 4 | |a Hindi health data |
650 | 0 | 4 | |a Hindi language |
650 | 0 | 4 | |a named entity |
650 | 0 | 4 | |a real coded genetic algorithm |
650 | 0 | 4 | |a ROUGE metric |
650 | 0 | 4 | |a summarization tool |
700 | 1 | |a Arora, A. |e author | |
700 | 1 | |a Jain, A. |e author | |
700 | 1 | |a Kumar, K.V. |e author | |
700 | 1 | |a Morato, J. |e author | |
700 | 1 | |a Yadav, D. |e author | |
773 | |t Applied Sciences (Switzerland) |