1. Matching Use cases
1.1. External Client Recipe List to Internal Master Food List (both heading and ingredient list)
1.1.1. which is the best match based on name
1.1.2. which is the best match based on name + ingredient
1.1.3. which is the best match based on additional information like food category, prepared food etc.
1.2. Match food data tables for subsequent merging
1.2.1. e.g. GI Dataset
1.2.2. FODMAP
1.2.3. CHROMIUM
1.3. deduplication of food lists
1.3.1. FNDDS
1.3.2. LEGACY
1.4. master ingredient list regeneration
2. Supporting Datasets
2.1. Food Processing Operations
2.1.1. Cooking - Wikipedia
2.1.1.1. methods
2.1.2. pickling
2.2. Categorization
2.2.1. Food Category
2.2.1.1. e.g. fruit, vegetable, baby food
2.2.1.2. Tags - Machine learning
2.2.1.2.1. e.g. breakfast
2.2.1.2.2. Mediterranean/ European etc
2.3. Thesaurus
2.3.1. infant milk powder / baby milk powder
2.3.2. red meat / meat/ beef / steak
2.4. Language Glossary
2.4.1. Italian
2.4.2. Chinese
2.4.3. Malaysian
2.4.4. Japanese
2.4.4.1. Tempura Ebi vs. Batter Coated Shrimp
3. Explainer
3.1. Explainer Rel. 1
3.2. Explainer Rel. 2
3.3. Explainer Rel. 3
3.3.1. Microbiome Explainer
3.3.2. Long Form Explainer
3.3.3. Short Form Explainer
3.4. Quality
3.4.1. Automated Evaluation of Explainer output
3.4.2. Gender Neutral
3.4.3. Correct disease of patient
4. Matching Strategy and Scoring
4.1. Output
4.1.1. Score
4.1.1.1. How to score
4.1.1.1.1. is it able to catch spelling errors
4.1.1.1.2. food processing aware
4.1.1.1.3. Able to impute CLIENT context
4.1.1.1.4. Language Glossary Aware
4.2. Types of Match
4.2.1. Food Term Match
4.2.1.1. food item matches but processing may not match (e.g. boiled BROCOLLI)
4.2.2. Food Term + Food Processing Match
4.2.2.1. e.g. boiled BROCOLLI
4.2.3. Food Term + Processing + Recipe Ingredient
4.3. Types of Precondition that can be invoked
4.3.1. Specify Food List
4.3.1.1. FNDDS, Legacy
4.3.2. Specify Category
4.3.2.1. fruit, vegetable, baby food
4.3.3. Term + Ingredient List
4.3.4. Match + Return Micronutrient Average of Item -( Average for Onion - White Onion + Red Onion)