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Remigio Ismael Hurtado Ortiz

Researcher

  • 45 Citations
  • 4 h-Index
20152019

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

Playful Interactive Microworlds As Therapeutic Support Tools Aimed At Children Under Risk ( Microludi V2 )

Pesantez Aviles, L. F., Hurtado Ortiz, R. I., Ingavelez Guerra, P. C., Quisi Peralta, D. F., Robles Bykbaev, V. E. & Timbi Sisalima, C. F.

17/06/15 → 17/06/16

Project: Research and Development

Research Output

  • 45 Citations
  • 4 h-Index
  • 5 Article
  • 3 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

    • 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

    • Hierarchical clustering for collaborative filtering recommender systems

    Chalco, C. I., Chasi, R. B. & Ortiz, R. H., 1 Jan 2019, Hierarchical clustering for collaborative filtering recommender systems. Ahram, T. Z. (ed.). p. 346-356 11 p. (Advances in Intelligent Systems and Computing; vol. 787).

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

    • 1 Scopus citations

    An efficient recommender system method based on the numerical relevances and the non-numerical structures of the ratings

    Zhu, B., Hurtado, R., Bobadilla, J. & Ortega, F., 31 Aug 2018, In : IEEE Access. 6, p. 49935-49954 20 p., 8453781.

    Research output: Contribution to journal › Article

    • 5 Scopus citations