Cuisine Transformation via Semantic Recipe Embeddings
Cross-cultural recipe transformation using neural networks and semantic embeddings. Published at ICDMW 2025.
Developed a neural network classifier to identify cuisine types from recipes, and an unsupervised ingredient substitution system using semantic embeddings — work done at the Complex Systems Lab, IIIT Delhi.
Key contributions:
Neural network classifier for cuisine type identification from recipe text
Unsupervised ingredient substitution via semantic embedding similarity
90% accuracy in cuisine preservation after cross-cultural transformation
Developed a neural network classifier to identify cuisine types from recipes. Created an unsupervised ingredient substitution method via semantic embeddings, achieving 90% accuracy in cuisine preservation after cross-cultural transformation.
@inproceedings{khanduri2025cross,title={Cross-Cultural Recipe Transformation Via Neural Network and Encoder-Based Models},author={Khanduri, Vibhuti Dhar and Goel, Mansi and Dabas, Lakshay and Agarwal, Harsh Kumar},booktitle={2025 IEEE International Conference on Data Mining Workshops (ICDMW)},pages={633--640},year={2025},organization={IEEE},}