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To extract similarity information, S<jats:sc>idle<\/jats:sc> first identifies <jats:italic>k<\/jats:italic> nearest neighbors in instance space and enhanced label space, respectively. Then, with these identified samples, S<jats:sc>idle<\/jats:sc> calculates the simple counting statistics based on their labels as well as a bias based on distance between the sample and these identified samples. Finally, the instance space is enriched with extracted similarity information to update instance space and enhanced label space. These three steps are iteratively conducted until convergence. Experiments validate the effectiveness of the proposed S<jats:sc>idle<\/jats:sc> approach.<\/jats:p>","DOI":"10.1007\/s11704-025-41432-y","type":"journal-article","created":{"date-parts":[[2025,10,17]],"date-time":"2025-10-17T02:47:38Z","timestamp":1760669258000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Similarity-based multi-dimensional multi-label classification"],"prefix":"10.1007","volume":"20","author":[{"given":"Zi-Zhan","family":"Gu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bin-Bin","family":"Jia","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Min-Ling","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,10,17]]},"reference":[{"key":"41432_CR1","doi-asserted-by":"publisher","first-page":"109357","DOI":"10.1016\/j.patcog.2023.109357","volume":"138","author":"B B Jia","year":"2023","unstructured":"Jia B B, Zhang M L. 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