Computational Techniques for Text Summarization based on Cognitive Intelligence
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Computational Techniques for Text Summarization based on Cognitive Intelligence
Umamaheswari, K.; Priya, V.
Taylor & Francis Ltd
12/2024
216
Mole
9781032442471
Pré-lançamento - envio 15 a 20 dias após a sua edição
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Preface
About This Book
1. Concepts of Text Summarization
2. Large-Scale Summarization Using Machine Learning Approach
3. Sentiment Analysis Approach to Text Summarization
4. Text Summarization Using Parallel Processing Approach
5. Optimization Approaches for Text Summarization
6. Performance Evaluation of Large-Scale Summarization Systems
7. Applications and Future Directions
Appendix A: Python Projects and Useful Links on Text Summarization
Appendix B: Solutions to Selected Exercises
Index
About This Book
1. Concepts of Text Summarization
2. Large-Scale Summarization Using Machine Learning Approach
3. Sentiment Analysis Approach to Text Summarization
4. Text Summarization Using Parallel Processing Approach
5. Optimization Approaches for Text Summarization
6. Performance Evaluation of Large-Scale Summarization Systems
7. Applications and Future Directions
Appendix A: Python Projects and Useful Links on Text Summarization
Appendix B: Solutions to Selected Exercises
Index
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Machine Learning;Deep Learning;Parallel Processing;Optimization;Extractive Summarization;Vector Space Model;Multi-objective Differential Evolution;Text Summarization;Cuckoo Search;Compromise Ranking Method;KNN Model;POS Tag;DBSCAN Algorithm;Multi-document Summarization;Summarization Systems;Perform Sentiment Analysis;LDA;Cuckoo Search Algorithm;User Reviews;Recurrent Neural Networks;Summarization Task;Automatic Text Summarization;Automatic Evaluation Tools;Longest Common Subsequence;Topic Modeling Technique;Artificial Bee Colony Optimization;Sentiment Analysis;Sentiment Score;MapReduce Framework;Reference Summary;Event Summarization
Preface
About This Book
1. Concepts of Text Summarization
2. Large-Scale Summarization Using Machine Learning Approach
3. Sentiment Analysis Approach to Text Summarization
4. Text Summarization Using Parallel Processing Approach
5. Optimization Approaches for Text Summarization
6. Performance Evaluation of Large-Scale Summarization Systems
7. Applications and Future Directions
Appendix A: Python Projects and Useful Links on Text Summarization
Appendix B: Solutions to Selected Exercises
Index
About This Book
1. Concepts of Text Summarization
2. Large-Scale Summarization Using Machine Learning Approach
3. Sentiment Analysis Approach to Text Summarization
4. Text Summarization Using Parallel Processing Approach
5. Optimization Approaches for Text Summarization
6. Performance Evaluation of Large-Scale Summarization Systems
7. Applications and Future Directions
Appendix A: Python Projects and Useful Links on Text Summarization
Appendix B: Solutions to Selected Exercises
Index
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Machine Learning;Deep Learning;Parallel Processing;Optimization;Extractive Summarization;Vector Space Model;Multi-objective Differential Evolution;Text Summarization;Cuckoo Search;Compromise Ranking Method;KNN Model;POS Tag;DBSCAN Algorithm;Multi-document Summarization;Summarization Systems;Perform Sentiment Analysis;LDA;Cuckoo Search Algorithm;User Reviews;Recurrent Neural Networks;Summarization Task;Automatic Text Summarization;Automatic Evaluation Tools;Longest Common Subsequence;Topic Modeling Technique;Artificial Bee Colony Optimization;Sentiment Analysis;Sentiment Score;MapReduce Framework;Reference Summary;Event Summarization
