Skip to main content
SpringerLink
Log in

Analysis of Knowledge Management in Industrial Sectors by Means of Neural Models

  • Conference paper
  • First Online:
10th International Conference on Soft Computing Models in Industrial and Environmental Applications

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 368))

Abstract

It is required for an organization, before successfully applying a Knowledge Management (KM) methodology, to develop and implement a knowledge infrastructure, consisting of people, organizational and technological systems. Up to now, few approaches have been proposed for such technological systems supporting KM in organizations. Present paper advances previous work by proposing neural projection models for the analysis of the KM status of companies from two different industrial sectors. Exploratory methods are applied to real-life case studies to know and understand the structure of KM data. Subsequently, the application of such models generates meaningful conclusions that allow experts to diagnose KM from two different points of view: companies on the one hand and industrial sectors on the other hand.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Herrero Á, Corchado E, Sáiz L, Abraham A (2010) DIPKIP: A connectionist knowledge management system to identify knowledge deficits in practical cases. Comput Intell 26:26–56

    Article  MATH  MathSciNet  Google Scholar 

  2. Durst S, Edvardsson IR (2012) Knowledge management in SMEs: a literature review. J Knowl Manag 16:879–903

    Article  Google Scholar 

  3. Levy M (2011) Knowledge retention: minimizing organizational business loss. J Knowl Manag 15:582–600

    Article  Google Scholar 

  4. Herrero Á, Corchado E, Jiménez A (2011) Unsupervised neural models for country and political risk analysis. Expert Syst Appl 38:13641–13661

    Google Scholar 

  5. Herrero Á, Corchado E, Gastaldo P, Zunino R (2009) Neural projection techniques for the visual inspection of network traffic. Neurocomputing 72:3649–3658

    Article  Google Scholar 

  6. Friedman JH, Tukey JW (1974) A projection pursuit algorithm for exploratory data-analysis. IEEE Trans Comput 23:881–890

    Article  MATH  Google Scholar 

  7. Hotelling H (1933) Analysis of a complex of statistical variables into principal components. J Educ Psychol 24:417–444

    Article  Google Scholar 

  8. Pearson K (1901) On lines and planes of closest fit to systems of points in space. Phil Mag 2:559–572

    Article  Google Scholar 

  9. Seung HS, Socci ND, Lee D (1998) The Rectified Gaussian Distribution. Adv Neural Inf Process Syst 10:350–356

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Civil Engineering, University of Burgos, Avenida de Cantabria s/n, 09006, Burgos, Spain

    Álvaro Herrero, Lourdes Sáiz-Bárcena & Miguel A. Manzanedo

  2. Departamento de Informática y Automática, Universidad de Salamanca, Plaza de la Merced s/n, 37008, Salamanca, Spain

    Emilio Corchado

Authors
  1. Álvaro Herrero
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Emilio Corchado
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Lourdes Sáiz-Bárcena
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Miguel A. Manzanedo
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Álvaro Herrero .

Editor information

Editors and Affiliations

  1. Department of Civil Engineering, University of Burgos, Burgos, Spain

    Álvaro Herrero

  2. C/ López Bravo 70, Pol. Ind. Villalonquejar, Technological Institute of Castilla y León, Burgos, Spain

    Javier Sedano

  3. Department of Civil Engineering, University of Burgos, Burgos, Spain

    Bruno Baruque

  4. University of Salamanca, Salamanca, Spain

    Héctor Quintián

  5. University of Salamanca, Salamanca, Spain

    Emilio Corchado

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this paper

Cite this paper

Herrero, Á., Corchado, E., Sáiz-Bárcena, L., Manzanedo, M.A. (2015). Analysis of Knowledge Management in Industrial Sectors by Means of Neural Models. In: Herrero, Á., Sedano, J., Baruque, B., Quintián, H., Corchado, E. (eds) 10th International Conference on Soft Computing Models in Industrial and Environmental Applications. Advances in Intelligent Systems and Computing, vol 368. Springer, Cham. https://doi.org/10.1007/978-3-319-19719-7_6

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-19719-7_6

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19718-0

  • Online ISBN: 978-3-319-19719-7

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation