Graduation Year

2024

Date of Submission

4-2024

Document Type

Campus Only Senior Thesis

Degree Name

Bachelor of Arts

Department

Mathematical Sciences

Reader 1

Mark Huber

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© 2024 Jacob Yep

Abstract

This senior thesis delves into the world of wine making, seeking to discover the fundamental features that contribute to the creation of a high quality wine. By analyzing an array of wines and their characteristics, this study identifies the primary features that are crucial in determining wine quality. Using different aspects of data analysis, features such as alcohol content, the amount of sulphates, and the amount of citric acid in a wine emerge as crucial components shaping the quality of wine. Furthermore, this paper presents the development of a wine recommender system designed to aid users in selecting wines based on their preferences. Utilizing a dataset consisting of a vast range of wines and their flavor profiles, a recommendation algorithm is created in order to process inputted flavor traits and output a list of the top 10 wines with the highest point scores out of 100. The recommender system employs machine learning techniques, including col-laborative filtering and natural language processing, to generate personalized recommendations tailored to individual tastes. By using ideas from both the analysis of wine features and the quantitative approach of the recommender system, this study provides a deep understanding of what makes up high quality wine and offers a practical tool for users to navigate the vast world of wine selection. This research contributes to the advancement of wine appreciation and assists both wine enthusiasts and novices in discovering wines that best suit their preferences.

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This thesis is restricted to the Claremont Colleges current faculty, students, and staff.

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