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61match
ficuseducation.com
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3 co-citations4 shared tech0 shared categoryonline-education
52match
hnmemorial.com
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2 co-citations0 shared tech2 shared categorysecondary-education
52match
jguides.com
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2 co-citations1 shared tech1 shared categoryeducation
49match
jamiemcglue.com
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2 co-citations4 shared tech0 shared categoryonline-education
47match
elevanceinstitute.com
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2 co-citations1 shared tech2 shared categoryeducation
46match
hjhawaii.com
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2 co-citations1 shared tech2 shared categorysecondary-education
46match
bosalajo.com
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2 co-citations1 shared tech1 shared categoryeducation
46match
afterhoursofficial.com
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2 co-citations1 shared tech1 shared categoryeducation
46match
dicowan.com
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1 co-citations1 shared tech2 shared categoryeducation
45match
devpeethclasses.com
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2 co-citations0 shared tech2 shared categorysecondary-education
45match
geocatchapp.com
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0 co-citations4 shared tech1 shared categoryeducation
43match
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2 co-citations1 shared tech1 shared categoryeducation
43match
campuschotu.com
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2 co-citations1 shared tech1 shared categoryeducation
43match
jackiebspeaks.com
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2 co-citations1 shared tech2 shared categoryeducation
42match
afghanamericanacademy.com
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2 co-citations0 shared tech1 shared categoryeducation
42match
barbarahouseman.com
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2 co-citations1 shared tech0 shared categoryadult-education
42match
guilfordalumni.com
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2 co-citations1 shared tech1 shared categorycollege-education
41match
elitelinemanacademy.com
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2 co-citations0 shared tech2 shared categoryeducation

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.