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Prof. Dr. Philipp Schaer | Information Retrieval Research Group at TH Köln — 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 Databases →

Domain	Match	Title	Country/Lang	Category	AI files	Contact	AI-protection
spielplatzkataster.net ↗	65 match 1 shared topics	geoVAL Informationssysteme	de	databases	robotsllmsaihumans	emailphone	none
hockinfosystems.com ↗	65 match 1 shared topics	Hock Informationssysteme	de	databases WordPress	robotsllmsaihumans	emailphone	none
cultos.org ↗	63 match 1 shared topics	CULTOS - Multimediales Wissensmanagement - Salzburg Research Forschungsgesellschaft	de	databases WordPress	robotsllmsaihumans	emailphone	none
koelnapi.de ↗	61 match 1 shared topics	Köln API – Data meets Citizen	Germany de	databases	robotsllmsaihumans	emailphone	none
culturebase.org ↗	61 match 1 shared topics	Willkommen im CultureBase Info-HUB - CultureBase	de	databases	robotsllmsaihumans	emailphone	none
23degrees.io ↗	61 match 1 shared topics	Create, find and reuse interactive data visualizations - 23°	de	databases	robotsllmsaihumans	emailphone	none
abkuerzung.org ↗	61 match 1 shared topics	Abkuerzung.org - Abkürzungen finden - Definition und Glossar	de	databases	robotsllmsaihumans	emailphone	none
bival.group ↗	61 match 1 shared topics	BIVAL \| Data Science	de	databases Wix	robots llmsaihumans	emailphone	none
rolffs.de ↗	61 match 1 shared topics	Datenbankentwicklung mit Microsoft Access und Lotus Notes, Tipps und Tricks, Downloads	Germany de	databases	robotsllmsaihumans	emailphone	none
coneda.net ↗	61 match 1 shared topics	ConedaKOR \| Coneda	de	databases WordPress	robotsllmsaihumans	emailphone	none
a-to-mic.com ↗	61 match 1 shared topics	Formular	de	databases	robotsllmsaihumans	emailphone	none
mader-online.org ↗	60 match 1 shared topics	Manfred's Schnipselkiste	de	databases	robotsllmsaihumans	emailphone	none
melusine.info ↗	60 match 1 shared topics	Willkommen! \| Melusine-Online-Archiv (MOA) V1.0 - Demoversion	de	databases Drupal	robotsllmsaihumans	emailphone	none
restaurierung-bw.de ↗	60 match 1 shared topics	Herzlich Willkommen » Datenbank Bauforschung/ Restaurierung	Germany de	databases	robotsllmsaihumans	emailphone	none
bigtestdata.online ↗	60 match 1 shared topics	Big Test Data \| Kistler DE	de	databases	robotsllmsaihumans	emailphone	none
bitwise.exposed ↗	60 match 1 shared topics	bitwise.exposed – about data	de	databases WordPress	robotsllmsaihumans	emailphone	none
accessunddatenexpertise-olsberg.org ↗	60 match 1 shared topics	Mentoring für Access & SQL Server Modernisierung \| On-Prem Experte	de	databases	robotsllmsaihumans	emailphone	none
minceddata.info ↗	60 match 1 shared topics	Mincing Data - Gain insight from data - Mincing Data - Gain Insight from Data	de	databases Jimdo	robotsllmsaihumans	emailphone	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.