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44match
dhnevins.com
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4 co-citations4 shared tech2 shared categoryfantasy
44match
jenaldenbooks.com
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2 co-citations5 shared tech2 shared categoryfantasy
42match
matthribar.com
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3 co-citations5 shared tech0 shared categorycomedy
39match
jackieweger.com
Jackie Weger - Home
2 co-citations5 shared tech2 shared categoryromance
39match
jamie-marchant.com
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3 co-citations3 shared tech3 shared categoryfantasy
37match
jaimeygrant.com
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2 co-citations4 shared tech2 shared categoryromance
37match
jenniferevergreen.com
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4 co-citations1 shared tech2 shared categoryfantasy
36match
julesparker.com
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3 co-citations4 shared tech2 shared categoryromance
36match
janelderauthor.com
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3 co-citations2 shared tech2 shared categoryromance
36match
holimoren.com
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2 co-citations4 shared tech1 shared categoryfantasy
35match
breanicolebond.com
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3 co-citations1 shared tech3 shared categoryfantasy
35match
elerigrace.com
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3 co-citations5 shared tech1 shared categoryromance
34match
kelliannmorgan.com
KELLI ANN MORGAN - Home
2 co-citations5 shared tech1 shared categoryromance
34match
handbookseries.com
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2 co-citations4 shared tech1 shared categoryromance
34match
jamiesalisbury.com
J R Salisbury - Historical Romance Author - Jamie Salisbury Romance Author
2 co-citations4 shared tech2 shared categoryromance
33match
hbreneau.com
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3 co-citations3 shared tech3 shared categoryfantasy
32match
corneliagrey.com
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2 co-citations4 shared tech1 shared categoryromance
31match
adrenalineradio.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.