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85match
haystackhostel.com
The Haystack Hostel
1 co-citations4 shared tech1 shared categoryhotels-and-motels
85match
aparthotelcare.com
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85match
apriliasvilla.com
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85match
bakermotel.com
Baker Motel
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85match
bapujinagar.com
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85match
bonairemotel.com
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1 co-citations2 shared tech1 shared categoryhotels-and-motels
85match
elisonresorts.com
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1 co-citations2 shared tech1 shared categoryhotels-and-motels
74match
guidedpathtravel.com
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71match
elafresidency.com
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1 co-citations2 shared tech1 shared categoryhotels-and-motels
70match
jamodaca.com
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70match
jobialcomforts.com
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70match
hhguesthouse.com
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1 co-citations2 shared tech1 shared categoryhotels-and-motels
70match
hobbithavenyelagiri.com
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1 co-citations2 shared tech1 shared categorybed-and-breakfasts
70match
greenislandcasa.com
Green Island Casa
1 co-citations2 shared tech1 shared categoryhotels-and-motels
70match
greenwoodlakerv.com
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1 co-citations2 shared tech1 shared categorycamping
70match
guestchalet.com
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1 co-citations2 shared tech1 shared categoryhotels-and-motels
70match
guesthouse-micaj.com
Guesthouse Micaj
1 co-citations2 shared tech1 shared categorybed-and-breakfasts
70match
3buhostel.com
3BU Hostel
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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.