Graph MayonnAIse in silico condiment synthesis Mayonnaise $12.5 - - PowerPoint PPT Presentation

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Mar 03, 2024 413 likes •616 views

Graph MayonnAIse in silico condiment synthesis Mayonnaise $12.5 billion industry by 2023 Regional / country-specific tastes Sensory profiles sweetness, saltiness, sourness yellowiness, shininess smoothness, viscosity

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Graph MayonnAIse

in silico condiment synthesis

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Mayonnaise

$12.5 billion industry by 2023
Regional / country-specific tastes
Sensory profiles

○ sweetness, saltiness, sourness ○ yellowiness, shininess ○ smoothness, viscosity

Vector representation

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Consumer Liking

Consumer surveys, e.g. 6.3 / 10
Country-specific regression models
New product > regression model > predicted consumer liking

...

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Don’t have a regression model for every country
How to predict consumer liking in new countries?

○ United States = 8.2 ○ Australia = 7.5 ○ Japan = 5.5 ○ Mexico = ?

Similarity-weighted sum

The Problem

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Cuisines Graph

Encode relationships between cuisines
Online data sources

○ yummly.co.uk ○ bbc.co.uk/food

Node labels

○ 22 cuisines ○ 18,000 recipes ○ 800 ingredients ○ 1,100 flavours

Undirected edges

England Fish & Chips Pie & Mash Cod Potato Oil Vinegar Pastry Pork Butter

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20,000 nodes and 197,000 edges
329,000,000,000 cuisine-cuisine paths

Connected Cuisines

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Map nodes into a vector space
Distance in the vector space represents structural similarity
Machine learning algorithms

○ DeepWalk ○ Node2Vec ○ TF-IDF

Graph Embeddings

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Neo4j Graph App

Braintree’s flagship graph analytics platform
Import, analyse and export data
Run the latest machine learning algorithms with ease
Implement algorithms in Python and run them on a Neo4j database

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Similarity scores

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Thank You

For more information on the GAMMA platform please contact:

gamma@braintree.com