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Semantic-Based System for Exercise Programming and Dietary Advice

Part of the Advances in Intelligent Systems and Computing book series (AISC,volume 1064)

Abstract

Growing health awareness results in interest in healthy eating and “fitness”. While information about exercising and dieting is readily accessible, it is difficult, for an inexperienced person, to find what is right for her/him in terms of both diet and exercise. The aim of this work is to introduce a system, based on semantic technologies, which addresses user goals with joint exercise programs and meal suggestions.

Keywords

  • Ontology
  • Semantic technologies
  • Inference
  • Nutrition
  • Fitness
  • Cloud
  • Scalability
  • High availability

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  • DOI: 10.1007/978-981-15-0339-9_10
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Notes

  1. 1.

    https://stronglifts.com/.

  2. 2.

    https://www.freeletics.com/.

  3. 3.

    https://lod-cloud.net.

  4. 4.

    https://jena.apache.org/.

  5. 5.

    https://www.w3.org/TR/rdf-sparql-query/.

  6. 6.

    https://www.w3.org/Submission/SWRL/.

  7. 7.

    https://github.com/Galigator/openllet.

  8. 8.

    https://github.com/stardog union/pellet.

  9. 9.

    https://www.docker.com.

  10. 10.

    https://kubernetes.io.

References

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Correspondence to Marcin Paprzycki .

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Mamatsashvili, GG., Ponichtera, K., Małkiński, M., Ganzha, M., Paprzycki, M. (2020). Semantic-Based System for Exercise Programming and Dietary Advice. In: Jain, L., Virvou, M., Piuri, V., Balas, V. (eds) Advances in Bioinformatics, Multimedia, and Electronics Circuits and Signals. Advances in Intelligent Systems and Computing, vol 1064. Springer, Singapore. https://doi.org/10.1007/978-981-15-0339-9_10

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  • DOI: https://doi.org/10.1007/978-981-15-0339-9_10

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-0338-2

  • Online ISBN: 978-981-15-0339-9

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