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SOCIETÀ DANTE ALIGHIERI Montauban – IL MONDO IN ITALIANO – Association pour la diffusion de la langue et de la culture italiennes — 18 websites ranked by shared content topics, category and on-page relevance.

Each result shows its full tech stack, contacts and AI-policy — not just a name · Browse all sites in Language Learning →

Domain	Match	Title	Country/Lang	Category	AI files	Contact	AI-protection
ieo31.com ↗	67 match 1 shared topics	IEO 31 – Promotion et diffusion de la langue et de la culture occitanes (cours d'occitan, librairie Tuta d'Oc, Festival Occitania) à Toulouse et en Haute-Garonne	fr	language-learning WordPress WooCommerce	robotsllmsaihumans	emailphone	none
provenceimmersion.com ↗	64 match 1 shared topics	Provence Immersion – École de Langues Côte d'Azur \| Cours de Langue Nice et Cannes	France~ fr	language-learning	robotsllmsaihumans	emailphone	none
interfaceitalie.com ↗	64 match 1 shared topics	Cours et formation italien pour les particuliers à Clermont Ferrand, Auvergne, 63	fr	language-learning	robotsllmsaihumans	emailphone	none
sixfeetunderfan.com ↗	64 match 1 shared topics	SFUF, allons à la découverte de la culture	fr	language-learning	robotsllmsaihumans	emailphone	none
asso-olala.com ↗	63 match 1 shared topics	Association OLALA \| Saumur	fr	language-learning WordPress WooCommerce	robotsllmsaihumans	emailphone	none
neolangue.com ↗	63 match 1 shared topics	NeoLangue \| Votre formation en langue et formation en anglais	fr	language-learning WordPress	robotsllmsaihumans	emailphone	none
2easy.fr ↗	63 match 1 shared topics	2 EASY – Centre de formation en langues	France fr	language-learning WordPress WooCommerce	robotsllmsaihumans	emailphone	none
ecole-club.ch ↗	63 match 1 shared topics	Cours de langues, cours de loisirs et formations - École-club Migros	Switzerland fr	language-learning Umbraco	robotsllmsaihumans	emailphone	none
hugoblanchet.com ↗	63 match 1 shared topics	Hugo Blanchet – Linguiste consultant – Chercheur en langues anciennes – Auteur	fr	language-learning WordPress	robotsllmsaihumans	emailphone	none
eskolim.org ↗	63 match 1 shared topics	Fédération des réseaux d’enseignement des langues régionales en immersion - Eskolim	fr	language-learning WordPress WooCommerce	robotsllmsaihumans	emailphone	none
voxea.com ↗	63 match 1 shared topics	École de français à Lausanne \| Cours de langues pour adultes \| VOXEA	fr	language-learning WordPress	robotsllmsaihumans	email phone	none
if-laos.org ↗	63 match 1 shared topics	Institut français du Laos – Cours, culture et débats d'idées au Laos	fr	language-learning WordPress	robotsllmsaihumans	emailphone	none
ccesp.com ↗	63 match 1 shared topics	Centre Culturel Espagnol de Rennes – Centro Cultural Español de Rennes	fr	language-learning WordPress	robotsllmsaihumans	emailphone	none
assimil-online.com ↗	63 match 1 shared topics	e-Méthode Numérique pour Apprendre une Langue - assimil.com	fr	language-learning PrestaShop	robotsllmsaihumans	emailphone	none
assprod.com ↗	63 match 1 shared topics	Centre Linguistique ASSPROD Douala \| Allemand, Italien, Anglais - Plus de 10 ans au service de la qualité	fr	language-learning	robotsllmsaihumans	email phone	none
assoflamuae.com ↗	62 match 1 shared topics	Association Flam UAE \| Le FLAM aux Emirats Arabes Unis	fr	language-learning WordPress WooCommerce	robotsllmsaihumans	emailphone	none
esperanto-montpellier.org ↗	62 match 1 shared topics	Espéranto Montpellier — Centre culturel espéranto de Montpellier	fr	language-learning	robotsllmsaihumans	emailphone	none
3cfle.com ↗	62 match 1 shared topics	3CFLE – Cours de Français Langue Étrangère	fr	language-learning WordPress WooCommerce	robotsllmsaihumans	email phone	none

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:

shared topics how many of the same fine‑grained content topics (IAB sub‑categories) both sites cover — the main signal.
same category whether they sit in the same business / industry category.
content & title how closely their titles and page descriptions line up in wording and meaning.

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.