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50match
hangangkorea.com
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3 co-citations0 shared tech2 shared categorybars-and-restaurants
49match
arribarriba.com
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47match
3westrest.com
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47match
cothams.com
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46match
julianosonline.com
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2 co-citations1 shared tech2 shared categorybars-and-restaurants
46match
lapromenadecafe.com
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1 co-citations3 shared tech2 shared categorybars-and-restaurants
46match
haywoodcafe.com
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1 co-citations3 shared tech2 shared categorybars-and-restaurants
46match
bagelanddeli.com
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1 co-citations3 shared tech2 shared categorybars-and-restaurants
45match
mancinosofpetoskey.com
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45match
manhattanchicago.com
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1 co-citations2 shared tech2 shared categorybars-and-restaurants
45match
bannersnh.com
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1 co-citations2 shared tech2 shared categorybars-and-restaurants
44match
lapiazzapizzamenu.com
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0 co-citations5 shared tech2 shared categorybars-and-restaurants
44match
mamasrevenge.com
Mama's Revenge Burritos Quesadillas Tex-Mex
3 co-citations4 shared tech2 shared categorybars-and-restaurants
44match
grappinonaples.com
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1 co-citations4 shared tech2 shared categorybars-and-restaurants
44match
guidoscozumel.com
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1 co-citations4 shared tech2 shared categorybars-and-restaurants
44match
elgringoslocos.com
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1 co-citations3 shared tech2 shared categorybars-and-restaurants
44match
5thavedelicarmel.com
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2 co-citations0 shared tech2 shared categorybars-and-restaurants
44match
mannasanfrancisco.com
Manna - Korean Cuisine - San Francisco
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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.