V. Priya, K. Umamaheswari
Computational Techniques for Text Summarization based on Cognitive Intelligence
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V. Priya, K. Umamaheswari
Computational Techniques for Text Summarization based on Cognitive Intelligence
- Gebundenes Buch
The book is concerned with contemporary methodologies used for automatic text summarization. It proposes interesting approaches to solve well-known problems on text-summarization using computational intelligence (CI) techniques including cognitive approaches.
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The book is concerned with contemporary methodologies used for automatic text summarization. It proposes interesting approaches to solve well-known problems on text-summarization using computational intelligence (CI) techniques including cognitive approaches.
Produktdetails
- Produktdetails
- Verlag: Taylor & Francis Ltd
- Seitenzahl: 216
- Erscheinungstermin: 17. März 2023
- Englisch
- Abmessung: 158mm x 237mm x 19mm
- Gewicht: 428g
- ISBN-13: 9781032392820
- ISBN-10: 1032392827
- Artikelnr.: 66739431
- Verlag: Taylor & Francis Ltd
- Seitenzahl: 216
- Erscheinungstermin: 17. März 2023
- Englisch
- Abmessung: 158mm x 237mm x 19mm
- Gewicht: 428g
- ISBN-13: 9781032392820
- ISBN-10: 1032392827
- Artikelnr.: 66739431
V. Priya is presently working as an assistant professor in, the department of computer science and engineering, Dr. N. G. P. Institute of Technology, Coimbatore, India. Her areas of research include text summarization using map-reduce and optimization along with an application. She has taught courses such as big data, data warehousing, and mining, operating systems, data management, and analytics at undergraduate and graduate levels. She has published research papers in journals of national and international repute. K. Umamaheswari is currently working as a professor and head of, the department of information technology, PSG College of Technology, India. She has more than twenty-five years of teaching experience and has published more than a hundred papers in journals and conferences of national and international repute. Her research interests include data mining, cognitive networks, text mining, and information retrieval. She is the senior editor for the National Journal of Technology and reviewers for many national and international journals.
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
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