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네이버 · ranked by category · tech stack · backlink co-citation
59match
bangsan365.com
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1 co-citations1 shared tech1 shared categoryshopping
55match
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55match
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hi-msmall.com
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1 co-citations0 shared tech1 shared categoryshopping
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46match
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40match
feykorea.com
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1 co-citations1 shared tech1 shared categoryshopping
39match
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1 co-citations2 shared tech1 shared categoryshopping
39match
misingmall.com
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1 co-citations2 shared tech1 shared categoryshopping
38match
ggumigga.com
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1 co-citations3 shared tech1 shared categoryshopping
38match
kizwood.com
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1 co-citations0 shared tech1 shared categoryshopping
38match
mandulove.com
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38match
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1 co-citations0 shared tech1 shared categoryshopping
38match
jiguhara.com
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1 co-citations0 shared tech1 shared categoryhousehold-supplies
38match
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1 co-citations0 shared tech1 shared categoryshopping
38match
hamchae.com
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How the match score works

Each match is a 0–100 similarity score — the higher it is, the more two sites resemble one another. It’s computed automatically from our own crawl data (never from what a site says about itself) by combining several independent signals, so a high score means several of them point the same way:

No single signal decides the result — they’re blended together. Treat the score as a way to rank candidates rather than an absolute percentage; the chips on each result show which signals contributed.