Automatic text summarization with maximal frequent sequences
At any time humans need accurate information to solve different problems. For example, how to perform a task, what happens in the news, what the hundreds of tweets say, etc. On the other hand, electronic information has exponentially growth; therefore the problem is how to discern in few minutes whi...
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| Formato: | Libro electrónico |
| Idioma: | Inglés |
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Ciudad de México :
Ediciones y Gráficos Eón
2013.
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| Colección: | Colección Biblioteca de Investigación Especializada. Área del conocimiento: Humanidades/Ingeniería.
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| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009429580906719 |
Tabla de Contenidos:
- Automatic text summarization with maximal frequent sequences
- Página legal
- Índice
- Abstract
- Resumen
- Introduction
- Chapter I
- I.1 Computational
- I.2 Text summarization
- I.3 Extractive text summarization
- I.4 Abstractive text summarization
- I.5 Applications of text
- I.6 Research problem
- Chapter II
- II.1 Text pre-processing
- II.2 Text representation
- II.3 Graph algorithms
- II.4 Genetic algorithms
- II.5 Clustering
- Chapter III
- III.1 Definitions
- III.2 New method using maximal
- III.3 New method using graph
- III.5 New method using clustering
- Chapter IV
- IV.1 Experimental
- IV.2 Experimental
- IV.3 Experimental
- Conclusions
- References
- Appendices.
