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OntoRecipe: An Ontology Focussed Semantic Strategy for Recipe Recommendation

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Digital Technologies and Applications (ICDTA 2022)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 454))

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Abstract

In present-day times there is a need for a recipe recommendation system to cater to the demanding culinary needs of several users around the globe. This paper proposes an ontology focused recipe recommendation approach by incorporating semantic models. Its deep learning infused using RNN classification. The dataset uses here is from Food.com Recipes and Interaction which contains 280 k+ recipes and 700 k+ recipe reviews which covers 18 years of user interaction and uploads. The dataset based on it increases a good number of auxiliary knowledge and uses pair of approaches like SemantoSim and Kullback-Leibler divergence under the Shuffled Frog-Leaping algorithm a knowledge-centric recipe is recommended. It shows that the proposed structure performs better than the other baseline approaches in terms of the F-Measure and False Discovery Rate having values 95.03 and 0.06.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, SRM Institute of Science and Technology, Ramapuram, Chennai, India

    Siddhant Singh

  2. Department of Computer Science and Engineering, National Institute of Technology, Tiruchirappalli, India

    Gerard Deepak

Authors
  1. Siddhant Singh
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  2. Gerard Deepak
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Corresponding author

Correspondence to Gerard Deepak .

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Editors and Affiliations

  1. Ecole Nationale des Sciences Appliquées, Fez, Morocco

    Saad Motahhir

  2. Faculty of Sciences, Sidi Mohamed Ben Abdellah University, Fez, Morocco

    Badre Bossoufi

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Singh, S., Deepak, G. (2022). OntoRecipe: An Ontology Focussed Semantic Strategy for Recipe Recommendation. In: Motahhir, S., Bossoufi, B. (eds) Digital Technologies and Applications. ICDTA 2022. Lecture Notes in Networks and Systems, vol 454. Springer, Cham. https://doi.org/10.1007/978-3-031-01942-5_3

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