Exploring Culinary Links with NLP and Knowledge Graphs

[This post is based on Nour al Assali‘s bachelor AI thesis]

Nour’s research explores the use of Natural Language Processing (NLP) and Knowledge Graphs to investigate the historical connections and cultural exchanges within global cuisines. The thesis “Flavours of History: Exploring Historical and Cultural Connections Through Ingredient Analysis Using NLP and Knowledge Graphs” describes a method for analyzing ingredient usage patterns across various cuisines by processing a dataset of recipes. Its goal is to trace the diffusion and integration of ingredients into different culinary traditions. The primary aim is to establish a digital framework for addressing questions related to culinary history and cultural interactions.

The methodology involves applying NLP to preprocess recipe data, focusing on extracting and normalizing ingredient names. The pipeline contains steps for stop word removal, token- and lemmatization, character replacements etc.

With the results, a Knowledge Graph is constructed to map relationships between ingredients, recipes, and cuisines. The approach also includes visualizing these connections, with an interactive map and other tools designed to provide insights into the data and answer key research questions. The figure below shows a visualisation of top ingredients per cuisine.

Case studies on ingredients such as pistachios, tomatoes, basil, olives, and cardamom illustrate distinct usage patterns and origins. The findings reveal that certain ingredients—like pistachios, basil, and tomatoes—associated with specific regions have gained widespread international popularity, while others, such as olives and cardamom, maintain strong ties to their places of origin. This research underscores the influence of historical trade routes and cultural exchanges on contemporary culinary practices and offers a digital foundation for future investigations into culinary history and food culture.

The code and dataset used in this research are available on GitHub: https://github.com/Nour-alasali/BPAI. The complete thesis can be found below.

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