Corpus composition research
Kanji Pair Research
Enter one kanji to discover other characters recorded in the same JMnedict name spellings, or enter two kanji to inspect that exact co-occurrence. Every count in this research view describes the imported corpus—not population popularity in Japan.
加
Jōyō · KANJIDIC grade 4 · 5 strokes
美add, addition, increase
Jōyō · KANJIDIC grade 3 · 9 strokes
Find exact-kanji names →beauty, beautiful
Recorded names
Name readings containing both characters
The pair only has to occur in the same written form; the two kanji are not required to be adjacent unless counted in the adjacency statistics above.
Surname
加々美
4 source-recorded spellings in this reading group contain both 加 and 美SurnameKagami
かがみ
冨加美
2 source-recorded spellings in this reading group contain both 加 and 美SurnameFukami
ふかみ
加美谷
1 source-recorded spelling in this reading group contain both 加 and 美SurnameKamiya
かみや
加美
1 source-recorded spelling in this reading group contain both 加 and 美SurnameKami
かみ
沙加美
1 source-recorded spelling in this reading group contain both 加 and 美SurnameSagami
さがみ
意加美
1 source-recorded spelling in this reading group contain both 加 and 美SurnameIgami
いがみ
加美谷
1 source-recorded spelling in this reading group contain both 加 and 美SurnameKamitani
かみたに
加美田
1 source-recorded spelling in this reading group contain both 加 and 美SurnameKamita
かみた
加美山
1 source-recorded spelling in this reading group contain both 加 and 美SurnameKamiyama
かみやま
池加美
1 source-recorded spelling in this reading group contain both 加 and 美SurnameIkegami
いけがみ
加美川
1 source-recorded spelling in this reading group contain both 加 and 美SurnameKamikawa
かみかわ
加美長
1 source-recorded spelling in this reading group contain both 加 and 美SurnameKaminaga
かみなが
加々美
1 source-recorded spelling in this reading group contain both 加 and 美Kakami
かかみ
Evidence boundary
Co-occurrence is not popularity or etymology
The pair relation comes from exact JMnedict source rows through the compact kanji-usage index. KANJIDIC2 contributes character metadata only. A high corpus count can reflect dictionary coverage and should not be read as a national usage frequency.