Culinary Recipe Recommendation based on Text Analytics

  • Authors

    • Jiheon Hong
    • Heejung Lee
    2018-09-15
    https://doi.org/10.14419/ijet.v7i4.4.19591
  • Text mining, Recommender system, Food recipe

  • Abstract

    Many researchers and practitioners have studied the recipe recommendation, and that problem is not only to find the tasty dishes based on the individual’s preference, but also to generate new ones. In the digital age, understanding and utilizing text data is one of the most important part in the knowledge discovery. In this paper, we proposed how to use text analysis in the recipe recommendation problem and provided the insights to design new recipes.

     

  • References

    1. [1] J. Lafferty, A. McCallum, and F. Pereira, Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data, Proceedings of International Conference on Machine Learning, 2001.

      [2] F. Shan and F. Pereira, Shallow Parsing with Conditional Random Fields, Proceedings of NAACL, 2013.

      [3] C. Y. Teng, Y. R. Lin, and L. A. Adamic, Recipe recommendation using ingredient networks, Proceedings of the 4th ACM Web Science Conference, 2012.

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  • How to Cite

    Hong, J., & Lee, H. (2018). Culinary Recipe Recommendation based on Text Analytics. International Journal of Engineering & Technology, 7(4.4), 5-6. https://doi.org/10.14419/ijet.v7i4.4.19591

    Received date: 2018-09-12

    Accepted date: 2018-09-12

    Published date: 2018-09-15