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However, there is a growing trend in the literature to use RVIs when selecting a Similarity Paradigm (SP) for clustering\u2014the combination of normalisation procedure, representation method and distance measure which affects the computation of object dissimilarities used in clustering. Despite the growing prevalence of this practice, there has been no empirical or theoretical investigation into the suitability of RVIs for this purpose. Moreover, since RVIs are computed using object dissimilarities, it remains unclear how they would need to be implemented for fair comparisons of different SPs.<\/jats:p>\n          <jats:p>This study presents the first comprehensive investigation into the reliability of RVIs for SP selection. We conducted extensive experiments with seven popular RVIs on over 2.7 million clustering partitions of synthetic and real-world datasets, encompassing feature-vector and time-series data. We identified fundamental conceptual limitations undermining the use of RVIs for SP selection, and our empirical findings confirmed this predicted unsuitability. Among our recommendations, we suggest instead that practitioners select SPs by using external validation on high quality labelled datasets or carefully designed outcome-oriented objective criteria, both of which should be informed by careful consideration of dataset characteristics and domain requirements. Our findings have important implications for clustering methodology and evaluation, suggesting the need for more rigorous approaches to SP selection in clustering applications.<\/jats:p>","DOI":"10.1145\/3748726","type":"journal-article","created":{"date-parts":[[2025,7,16]],"date-time":"2025-07-16T13:26:05Z","timestamp":1752672365000},"page":"1-53","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["On the Use of Relative Validity Indices for Comparing Clustering Approaches"],"prefix":"10.1145","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-5894-2281","authenticated-orcid":false,"given":"Luke W.","family":"Yerbury","sequence":"first","affiliation":[{"name":"School of Information and Physical Sciences, The University of Newcastle, Callaghan, Australia and Energy Centre, The Commonwealth Scientific and Industrial Research Organisation (CSIRO), Mayfield West, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0266-3492","authenticated-orcid":false,"given":"Ricardo J. 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