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SmartData: An Intelligent Decision Support System to Predict the Readers Permanence in News

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Intelligent Systems and Applications (IntelliSys 2021)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 295))

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  • The original version of this chapter was revised: The chapter authors’ given and family name has been correctly identified and updated. The correction to this chapter is available at https://doi.org/10.1007/978-3-030-82196-8_61

Abstract

This article proposes a hybrid intelligent system based on the application and combination of Artificial Intelligence methods as a decision support tool. The objective of this study is to exploit the advantages of the constituent algorithms, to predict the permanence rates of readers in news from a digital media. With this, the editor will be able to decide whether to publish a news item or not. To evaluate the effectiveness of the hybrid intelligent system, data from a reference digital media is used. In addition, a series of performance metrics is calculated, where 88% effective is demonstrated with the predicted results.

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Change history

  • 03 August 2021

    In the original version of the book, the following correction has been updated: In Chapter 25, the given and family name for the authors Jessie Caridad Martín Sujo, Elisabet Golobardes i Ribé, Xavier Vilasís Cardona, Virginia Jiménez Ruano, Javier Villasmil López now been correctly identified and updated. The book and the chapter have been updated with the change.

Notes

  1. 1.

    Published in Digital NewsReport. Available in<https://www.digitalnewsreport.es/2019/el-45-de-los-usuarios-elige-la-television-como-medio-principal-para-informarse-mientras-el-40-opta-por-las-fuentes-online/>.

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Acknowledgments

This work has been financed by the Ministry of Economy, Industry and Competitiveness of the Government of Spain and the European Regional Development Fund with the help n\(^o\) RTC-2016-5503-7 (MINECO / FEDER, EU) for the project Smart Data Discovery and Natural Language Generation for Digital Media Performance. And it has also been possible thanks to our partners Agile; Easy at University of Girona and DS4DS research group at La Salle - Ramon Llull University.

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Authors and Affiliations

  1. Research Group on Data Science for the Digital Society (DS4DS), La Salle -Universitat Ramon Llull, 08024, Barcelona, Spain

    Jessie Caridad Martín Sujo, Elisabet Golobardes i Ribé, Xavier Vilasís Cardona, Virginia Jiménez Ruano & Javier Villasmil López

Authors
  1. Jessie Caridad Martín Sujo
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  2. Elisabet Golobardes i Ribé
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  3. Xavier Vilasís Cardona
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  4. Virginia Jiménez Ruano
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  5. Javier Villasmil López
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Corresponding author

Correspondence to Jessie Caridad Martín Sujo .

Editor information

Editors and Affiliations

  1. Faculty of Science and Engineering, Saga University, Saga, Japan

    Kohei Arai

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Martín Sujo, J.C., Golobardes i Ribé, E., Vilasís Cardona, X., Jiménez Ruano, V., Villasmil López, J. (2022). SmartData: An Intelligent Decision Support System to Predict the Readers Permanence in News. In: Arai, K. (eds) Intelligent Systems and Applications. IntelliSys 2021. Lecture Notes in Networks and Systems, vol 295. Springer, Cham. https://doi.org/10.1007/978-3-030-82196-8_25

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