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Intellectual Property in Colombian Museums: An Application of Machine Learning

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Intelligence Science and Big Data Engineering. Big Data and Machine Learning (IScIDE 2019)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 11936))

Abstract

The purpose of this research is to answer the following guiding question: how can the behavior of museum networks in Colombia be predicted with respect to the protection of intellectual property (copyright, confidential information and use of patents, domain names, industrial designs, use of trademarks) and the interaction of different types of proximity (geographical, organizational, relational, cognitive, cultural and institutional), based on the use of supervised learning algorithms?

Among the main findings are that the best learning algorithms to predict the behavior of networks, considering different target variables are the AdaBoost, the naive Bayes and CN2 rule inducer.

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Notes

  1. 1.

    According to Resolution 1975 of 2013 of the Ministry of Culture, a thematic network is an “organizational form that links the different agents of the museum sector according to the themes of interest, common administrative forms and typologies of collection” (article 1).

  2. 2.

    In accordance with Resolution 1975 of 2013 of the Ministry of Culture, a territorial network is an “organizational form that links the different agents of the museum sector located in the different territories of the country” (article 1).

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Author information

Authors and Affiliations

  1. Universidad Nacional de Colombia, Bogotá, Colombia

    Jenny Paola Lis-Gutiérrez & Álvaro Zerda Sarmiento

  2. Universidad de la Costa, Barranquilla, Colombia

    Amelec Viloria

Authors
  1. Jenny Paola Lis-Gutiérrez
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  2. Álvaro Zerda Sarmiento
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  3. Amelec Viloria
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Corresponding author

Correspondence to Jenny Paola Lis-Gutiérrez .

Editor information

Editors and Affiliations

  1. Nanjing University of Science and Technology, Nanjing, China

    Zhen Cui

  2. Nanjing University of Science and Technology, Nanjing, China

    Jinshan Pan

  3. Nanjing University of Science and Technology, Nanjing, China

    Shanshan Zhang

  4. Nanjing University of Science and Technology, Nanjing, China

    Liang Xiao

  5. Nanjing University of Science and Technology, Nanjing, China

    Jian Yang

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Lis-Gutiérrez, J.P., Zerda Sarmiento, Á., Viloria, A. (2019). Intellectual Property in Colombian Museums: An Application of Machine Learning. In: Cui, Z., Pan, J., Zhang, S., Xiao, L., Yang, J. (eds) Intelligence Science and Big Data Engineering. Big Data and Machine Learning. IScIDE 2019. Lecture Notes in Computer Science(), vol 11936. Springer, Cham. https://doi.org/10.1007/978-3-030-36204-1_24

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  • DOI: https://doi.org/10.1007/978-3-030-36204-1_24

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  • Publisher Name: Springer, Cham

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