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What the mapping measured
MOON built the mapping from ingredient lists collected from Olive Young product search results across 12 keyword categories: toner, cream, sunscreen, cleanser, sheet mask, cushion, lip, shampoo, body lotion, eye cream, essence, and lotion. The author reports 49,843 ingredient entries across 966 products. These are author-reported results from a convenience sample of search listings, not a census of Korean cosmetics or a regulator-validated benchmark.
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| Measure | Reported result | What it means |
|---|---|---|
| Ingredient-entry match rate | 96.7% of 49,843 entries | An individual ingredient entry received an English name. |
| Products with every ingredient matched | 641 of 966 products (66%) | About one in three products had at least one unmatched entry. |
| Median product | Fully matched, according to the author | The typical product in this sample had all entries mapped, even though the overall complete-product share was 66%. |
| Lowest-performing tenth | Around 92% matched, according to the author | Even in the weakest tenth, most individual entries still received a match; this does not mean those products were complete. |
The rates answer different questions. Entry-level coverage counts each ingredient position; complete-product coverage counts a product as successful only if every position is matched. A product with 20 mapped entries and one unmatched one contributes a strong entry-level result but does not count as fully translated.
The source data came from Korea’s Ministry of Food and Drug Safety (MFDS). Its API catalog describes fields for standard ingredient name, English name, CAS number, origin or definition, and synonyms; it lists REST API access in JSON or XML, free use, real-time updates, and no use-scope restriction. See the MFDS open-data API listing. MOON reports 21,945 standard ingredient names in the source and a lookup map of about 24,000 names after including synonyms. The exact API behavior and the current live scraper were not independently verified here.
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How to translate a Korean ingredient name
For a practical first pass, match the Korean name against a recognized ingredient-name source and preserve the original alongside the English result. The MFDS mapping described here is one data-cleaning approach, not a substitute for checking the label, the target market’s naming convention, or regulatory requirements.
- Keep the original string. Save each Korean label entry unchanged before cleaning it. That lets you audit the result and prevents normalization from erasing potentially meaningful text.
- Try an exact lookup first. MOON found that aggressive cleanup could discard valid details because some legitimate names contain parentheses. Search the raw name before stripping anything.
- Normalize only for a second lookup. If there is no match, remove attached amounts, ignore text after a footnote marker, account for extra spaces or stray quotation marks, and try a second index with hyphens removed. The author also encountered Latin-letter case variation. Do not overwrite the raw label with this normalized form.
- Handle synonyms carefully. The MFDS source includes synonyms, but the English output may choose one preferred name. A market may use another accepted form; MOON gives “Aqua” and “Water” as an example of different English naming preferences.
- Return unmatched entries as unmatched. Keep the Korean text and mark the English value as null or unresolved rather than guessing from a similar-looking name.
- Check list alignment. If you build arrays of Korean and English names, keep them in the same order and track both total ingredient count and number of successful matches. This makes missing positions visible.
When parsing English synonyms, MOON split alternatives on a comma followed by a letter, while preserving commas internal to names such as “1,2-Hexanediol.” That distinction is useful in automated data cleaning: splitting every comma would incorrectly break some ingredient names.
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What broke exact-name matching
Ingredient labels are written for people, not guaranteed to be canonical database keys. The author found that direct exact-name lookup failed on strings containing amounts attached to names, parenthetical concentration notes, footnote markers, omitted hyphens, inconsistent Latin-letter capitalization, extra spaces, and quotation marks introduced by spreadsheet copies.
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A disciplined matching system should therefore distinguish three outcomes: an exact or synonym match, a normalized match that can be reviewed, and no defensible match. Treating all near-matches as certain translations may make the coverage figure look better while making the output less trustworthy.
What appeared often in this Olive Young sample
MOON also reported ingredient frequencies within particular keyword-search categories and across the 966 sampled products. These are descriptive figures for the author’s search-result sample, not prevalence estimates for Korean products as a whole.
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| Finding | Sample and denominator |
|---|---|
| Water appeared in 94%, Glycerin in 84%, Butylene Glycol in 81%, 1,2-Hexanediol in 81%, and Ethylhexylglycerin in 68%. | Products in the 966-product sample; MOON, 2026. |
| Diethylamino Hydroxybenzoyl Hexyl Benzoate appeared in 68%, and Ethylhexyl Triazone in 67%. | Sunscreen keyword-search results in the sample; MOON, 2026. |
| Niacinamide appeared in 90%, and Adenosine in 86%. | Cushion keyword-search results in the sample; MOON, 2026. |
| Salicylic Acid appeared in 55%. | Shampoo keyword-search results in the sample; MOON, 2026. |
| Salicylic Acid appeared in 4%. | Results across the other sampled categories, according to MOON, 2026. |
The sunscreen figures should not be read as a current regulatory determination. MOON compared the two filters with the FDA’s permitted sunscreen-active list, but a database frequency and an author’s comparison do not establish a product’s legal status. Regulatory rules differ by market and can change; consult the applicable current regulator information for the product’s jurisdiction.
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A translated label is a naming result. It does not assess an ingredient’s purpose, concentration, exposure, or suitability for a particular person, and it cannot establish that two products sold in different markets have the same formula. Even a correct common name may be presented differently by market-specific ingredient nomenclature.
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The Korea Cosmetic Association (KCIA) describes its ingredient dictionary as a name-standardization resource and says it does not judge an ingredient’s purpose or whether it may be used. Its ingredient dictionary is therefore useful for naming, not as a safety clearance. Likewise, the technical INCIDB data dictionary warns that a missing match is not proof an ingredient is permitted or unregulated and that botanical CAS-number matches can be ambiguous. A CAS number is a useful identifier, but it is not always enough to settle the identity of a botanical entry.
To compare a Korean label with a US or EU ingredient list, first compare names and list positions, then investigate discrepancies separately. Do not infer that a missing English name means the ingredient is prohibited, nor that a familiar translation establishes compliance. The mapping study does not independently validate formulas or determine legality in any destination market.
How to interpret the coverage figures
- They describe Olive Young search listings. The 12 keyword searches were not curated category catalogs, and some results were off-category.
- They are not market-wide coverage estimates. Different retailers, product types, label styles, and languages could produce different match rates.
- They are author-reported measurements. No independent study or regulator validation of this match-rate benchmark was identified in the sources used for this article.
- They depend on the source’s English naming choices. MFDS’s first supplied English name may not be the preferred term in every market.
A reproducible way to inspect the underlying data
MOON describes the mapping as part of an Olive Young Scraper on Apify. The reported sample input uses search mode, keywords, product-detail inclusion, and a maximum item count; the output retains Korean and English ingredient arrays in matching order and includes an ingredient count and English-match count. Those details provide a way to think about reproducing the analysis, but the listing and current API behavior were not independently verified. The reported results should be attributed to MOON’s 2026 sample rather than treated as a fresh audit of the live service.
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