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Simulation studies on synthetic data are popular because important features of the data sets, such as the overlap between clusters, or the variation in cluster shapes, can be effectively varied. Unfortunately, creating evaluation scenarios is often laborious, as practitioners must translate higher-level scenario descriptions like \u201cclusters with very different shapes\u201d into lower-level geometric parameters such as cluster centers, covariance matrices, etc. To make benchmarks more convenient and informative, we propose synthetic data generation based on direct specification of high-level scenarios, either through verbal descriptions or high-level geometric parameters. Our open-source Python package\n                    <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"https:\/\/repliclust.org\" ext-link-type=\"uri\">https:\/\/repliclust.org<\/jats:ext-link>\n                    implements this workflow, making it easy to set up interpretable and reproducible benchmarks for cluster analysis. A demo of data generation from verbal inputs is available at\n                    <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"https:\/\/demo.repliclust.org\" ext-link-type=\"uri\">https:\/\/demo.repliclust.org<\/jats:ext-link>\n                    .\n                  <\/jats:p>","DOI":"10.1007\/s00357-025-09501-w","type":"journal-article","created":{"date-parts":[[2025,4,1]],"date-time":"2025-04-01T17:07:54Z","timestamp":1743527274000},"page":"517-543","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Natural Language-Based Synthetic Data Generation for Cluster Analysis"],"prefix":"10.1007","volume":"42","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-7499-148X","authenticated-orcid":false,"given":"Michael J.","family":"Zellinger","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Peter","family":"B\u00fchlmann","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,3,31]]},"reference":[{"key":"9501_CR1","doi-asserted-by":"crossref","unstructured":"Aggarwal, C.\u00a0C., Hinneburg, A., & Keim, D.\u00a0A. 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