Topic Detection and Classification in Social Networks [electronic resource] : The Twitter Case / by Dimitrios Milioris.

Por: Milioris, Dimitrios [author.]Colaborador(es): SpringerLink (Online service)Tipo de material: TextoTextoEditor: Cham : Springer International Publishing : Imprint: Springer, 2018Edición: 1st ed. 2018Descripción: XVI, 105 p. 38 illus., 25 illus. in color. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9783319664149Tema(s): Electrical engineering | Computational intelligence | Optical data processing | Computer organization | Natural language processing (Computer science) | Communications Engineering, Networks | Computational Intelligence | Computer Imaging, Vision, Pattern Recognition and Graphics | Computer Systems Organization and Communication Networks | Natural Language Processing (NLP)Formatos físicos adicionales: Printed edition:: Sin título; Printed edition:: Sin título; Printed edition:: Sin títuloClasificación CDD: 621.382 Clasificación LoC:TK1-9971Recursos en línea: Libro electrónicoTexto
Contenidos:
Introduction -- Background and Related Work -- Joint Sequence Complexity -- Text Classification via Compressive Sensing -- Extension of Joint Complexity and Compressive Sensing -- Conclusion.
En: Springer Nature eBookResumen: This book provides a novel method for topic detection and classification in social networks. The book addresses several research and technical challenges that are currently being investigated by the research community, from the analysis of relations and communications between members of a community, to quality, authority, relevance and timeliness of the content, traffic prediction based on media consumption, spam detection, to security, privacy and protection of personal information. Furthermore, the book discusses innovative techniques to address those challenges and provides novel solutions based on information theory, sequence analysis and combinatorics, which are applied on real data obtained from Twitter.
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Acceso multiusuario

Introduction -- Background and Related Work -- Joint Sequence Complexity -- Text Classification via Compressive Sensing -- Extension of Joint Complexity and Compressive Sensing -- Conclusion.

This book provides a novel method for topic detection and classification in social networks. The book addresses several research and technical challenges that are currently being investigated by the research community, from the analysis of relations and communications between members of a community, to quality, authority, relevance and timeliness of the content, traffic prediction based on media consumption, spam detection, to security, privacy and protection of personal information. Furthermore, the book discusses innovative techniques to address those challenges and provides novel solutions based on information theory, sequence analysis and combinatorics, which are applied on real data obtained from Twitter.

UABC ; Temporal ; 01/01/2021-12/31/2023.

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