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This method consists of two main parts. The first part is the proposed incomplete data weighted classification tree algorithm. In the first part, an incomplete data weighted classification tree is proposed, and the incomplete data set is classified using this tree. The data classified in the first part serves as the basis for the second step of the query. The second part proposes a skyline query algorithm for multidimensional incomplete data. The concept of optimal virtual points has been recently introduced, effectively reducing the number of comparisons of a large amount of data, thereby improving the query efficiency for incomplete data. Theoretical research and experimental analysis have shown that the proposed method can perform skyline queries for multidimensional incomplete data well, with high query efficiency and accuracy of the algorithm.<\/jats:p>","DOI":"10.1186\/s40537-024-00923-8","type":"journal-article","created":{"date-parts":[[2024,5,12]],"date-time":"2024-05-12T12:01:29Z","timestamp":1715515289000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Skyline query under multidimensional incomplete data based on classification tree"],"prefix":"10.1186","volume":"11","author":[{"given":"Dengke","family":"Yuan","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Liping","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Song","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guanglu","family":"Sun","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,5,12]]},"reference":[{"issue":"2","key":"923_CR1","doi-asserted-by":"publisher","first-page":"219","DOI":"10.26599\/TST.2019.9010060","volume":"26","author":"J Li","year":"2021","unstructured":"Li J, Sai AMVV, Cheng X, et al. 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