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A personal knowledge management metamodel based on semantic analysis and social information

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Abstract

This article describes the development of a functional architecture for personal knowledge management (PKM), defined from the lessons-learnt concept registered in a mass-use social network analyzed with an algorithm of machine learning. This functional architecture applies, in practical manner, the implementation of a registry system of the personal lessons learnt in the cloud through a Facebook social network. The process starts by acquiring data from the connection to a non-relational database (NoSql) in Amazon’s SimpleDB and to which a complementary analysis algorithm of machine learning has been configured for the semantic analysis of the information registered from lessons learnt and, thus, to study the generation of organizational knowledge management from PKM. The result is the design of a functional architecture that permits integrating the Web 2.0 application and a semantic analysis algorithm from unstructured information by applying machine learning techniques.

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Authors and Affiliations

  1. Universidad de Oviedo, Oviedo, Spain

    J. F. López-Quintero

  2. Departamento de Informática, Universidad de Oviedo, Oviedo, Spain

    J. M. Cueva Lovelle & V. García-Díaz

  3. Escuela Superior de Ingeniería y Tecnología, Universidad Internacional de La Rioja (UNIR), Logroño, Spain

    R. González Crespo

Authors
  1. J. F. López-Quintero
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  2. J. M. Cueva Lovelle
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  3. R. González Crespo
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  4. V. García-Díaz
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Corresponding author

Correspondence to R. González Crespo.

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The authors declare that they have no conflict of interest.

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This article does not contain any studies with human participants performed by any of the authors.

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Communicated by V. Loia.

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López-Quintero, J.F., Cueva Lovelle, J.M., González Crespo, R. et al. A personal knowledge management metamodel based on semantic analysis and social information. Soft Comput 22, 1845–1854 (2018). https://doi.org/10.1007/s00500-016-2437-y

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