This study addresses the challenge of large-scale, multi-label recipe classification us- ing a real-world dataset of over 600,000 recipes collected from heterogeneous sources. The raw data exhibited significant noise, ...

The convergence of artificial intelligence with creative expression has given rise to the emerging field of Computational Creativity, a domain that explores the capacity of machines to generate innovative and aesthetically ...

This semester had the main objective of thoroughly rectifying Recipe DB 2 and its backend with special attention towards issues in the back-end architecture of the API dashboard. The abnormal functioning of Elasticsearch ...

Cooking is a quintessential creative pursuit with profound significance for humanity. Food and cooking transcend mere sensory pleasure and have serious nutrition and public health outcomes. Beyond being linked to the ...

In response to the escalating demand for the generation of novel and diverse cooking recipes, this research in Natural Language Processing introduces a new tool—Ratatouille. The tool utilizes various Deep Learning models, ...

The project aims to develop the Chef Turing Test to assess a machine's capacity to emulate a human chef's culinary skills and knowledge. This test encompasses various criteria, including recipe creation, ingredient knowledge, ...

With growing diversity in personal food preference and regional cuisine style, personalized information systems that can transform a recipe into any selected regional cuisine style that a user might prefer would help food ...

This project focuses on developing a robust Named Entity Recognition (NER) system tailored for recipe ingredient phrases, a critical task in computational gastronomy. The proposed ap- proach employs transformer-based models ...

The project aims to create an innovative food product search and prediction system that enables users to explore a comprehensive database of 900,000 food items. Each product is enriched with metadata, including its name, ...