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Automatic text summarization with maximal frequent sequences

Nikolaevna Ledeneva, Yulia; García Hernández, René · Ediciones y Gráficos Eón · 2013

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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 which of the thousands of pages actually contains the searched information. As in this summary, the human has included a summary made by the same author of the work in order that future readers can find in it the most interesting information, without having to read it. For this, the human has learnt to make summaries intuitively, however a computer requires complex methods to "understand" what is relevant information contained in the original text. The complexity of the problem increases if the challenge is to develop methods that could work in the lenguage and domain independant way or with orthographic errors, as sometimes happens with social media. In this book, novel computational methos are presented which permits automatically obtain text summaries in the laguage independent way with a high quality for its similarity to those generated by humans. El ser humano en todo momento necesita información precisa en diferentes circunstancias. Por ejemplo, para realizar una tarea, saber qué sucedió en las noticias o qué dicen los cientos de tweets, etc. Por otro lado, la información electrónica crece exponencialmente y el problema es cómo determinar en poco tiempo los documentos de interés. Las personas han incluido resúmenes de diversas obras para que sea posible encontrar en pocas palabras la información mas importante. Para ello, han aprendido a efectuar esta labor de manera intuitiva; sin embargo, las computadores requieren procedimientos complejos para tratar de "entender" cuáles son los datos relevantes del texto original. El reto es desarrollar métodos que funcionen independientemente del lenguaje o dominio de los textos, incluso si éstos son informales o tienen faltas de ortografía, como llega a suceder en las redes sociales. En este libro se presentan métodos computacionales novedosos que hacen frente al desafio y permiten obtener resúmenes de texto de alta calidad por su parecido con los generados por un humano.

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APA 7

Nikolaevna Ledeneva, Y. & García Hernández, R. (2013). Automatic text summarization with maximal frequent sequences. Ediciones y Gráficos Eón. https://nodovox.com/record.php?id=379801

MLA

Nikolaevna Ledeneva, Yulia, and René García Hernández. Automatic text summarization with maximal frequent sequences. Ediciones y Gráficos Eón, 2013. https://nodovox.com/record.php?id=379801.

Chicago

Nikolaevna Ledeneva, Yulia and René García Hernández. 2013. Automatic text summarization with maximal frequent sequences. Ediciones y Gráficos Eón. https://nodovox.com/record.php?id=379801.

Harvard

Nikolaevna Ledeneva, Y. and García Hernández, R. 2013, Automatic text summarization with maximal frequent sequences, Ediciones y Gráficos Eón, available at: https://nodovox.com/record.php?id=379801 [Accessed 10 Aug. 2026].

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Resource details

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Title
Automatic text summarization with maximal frequent sequences
Author / contributors
Nikolaevna Ledeneva, Yulia; García Hernández, René
Publisher
Ediciones y Gráficos Eón
Publication year
2013
ISBN
ISBN electrónico: 9781512970944 · ISBN impreso: 9786078289509
Language
English

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