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Rodolfo Xavier Bojorque Chasi

Researcher

  • 38 Citations
  • 3 h-Index
20172020

Research output per year

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Projects

Provide UPS Prediction And Recommendation Models That Facilitate Academic Management By Incorporating Machine Learning Techniques Into The Institutional Database

Bojorque Chasi, R. X. & Hurtado Ortiz, R. I.

27/07/17 → 31/12/18

Project: Research and Development

Research Output

  • 38 Citations
  • 3 h-Index
  • 5 Conference contribution
  • 4 Article

Academic Quality Management System Audit Using Artificial Intelligence Techniques

Bojorque, R. & Pesántez-Avilés, F., 1 Jan 2020, Academic Quality Management System Audit Using Artificial Intelligence Techniques. Ahram, T. (ed.). p. 275-283 9 p. (Advances in Intelligent Systems and Computing; vol. 965).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

    • A comparative analysis of similarity metrics on sparse data for clustering in recommender systems

    Bojorque, R., Hurtado, R. & Inga, A., 1 Jan 2019, A comparative analysis of similarity metrics on sparse data for clustering in recommender systems. Ahram, T. Z. (ed.). p. 291-299 9 p. (Advances in Intelligent Systems and Computing; vol. 787).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

    • 1 Scopus citations

    Analysis of scientific production based on trending research topics. An Artificial Intelligence case study

    Bobadilla, J., Gutiérrez, A., Patricio, M. Á. & Bojorque, R. X., 1 Jan 2019, In : Revista Espanola de Documentacion Cientifica. 42, 1, e228.

    Research output: Contribution to journal › Article

    • 2 Scopus citations

    A new recommendation approach based on probabilistic soft clustering methods: A scientific documentation case study

    Hurtado, R., Bobadilla, J., Bojorque, R., Ortega, F. & Li, X., 1 Jan 2019, In : IEEE Access. 7, p. 7522-7534 13 p., 8594540.

    Research output: Contribution to journal › Article

    • 3 Scopus citations

    Clustering-based recommender system: Bundle recommendation using matrix factorization to single user and user communities

    Ortiz, R. H., Chasi, R. B. & Chalco, C. I., 1 Jan 2019, Clustering-based recommender system: Bundle recommendation using matrix factorization to single user and user communities. Ahram, T. Z. (ed.). p. 330-338 9 p. (Advances in Intelligent Systems and Computing; vol. 787).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution