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70match
margaretstreetbooks.com
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1 co-citations0 shared tech2 shared categorybooks-and-literature
65match
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65match
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65match
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62match
elainequave.com
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1 co-citations1 shared tech0 shared categoryart-and-photography
60match
gratitudology.com
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1 co-citations1 shared tech1 shared categorybooks-and-literature
55match
ivandevro.com
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1 co-citations1 shared tech1 shared categorybooks-and-literature
55match
aeonbookstore.com
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0 co-citations1 shared tech1 shared categorybooks-and-literature
55match
cayleeduskey.com
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0 co-citations1 shared tech1 shared categorybooks-and-literature
52match
kampptales.com
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52match
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0 co-citations1 shared tech2 shared categorybooks-and-literature
51match
mandyhouk.com
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0 co-citations1 shared tech2 shared categorybooks-and-literature
51match
manicmagicwriting.com
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0 co-citations1 shared tech2 shared categoryfiction
50match
jenniferherrerabooks.com
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50match
jeneedutary.com
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50match
joemanzello.com
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0 co-citations1 shared tech2 shared categorybooks-and-literature
50match
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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.