Matches in SemOpenAlex for { <https://semopenalex.org/work/W3080491161> ?p ?o ?g. }
- W3080491161 endingPage "312" @default.
- W3080491161 startingPage "280" @default.
- W3080491161 abstract "Abstract For high-dimensional datasets in which clusters are formed by both distance and density structures (DDS), many clustering algorithms fail to identify these clusters correctly. This is demonstrated for 32 clustering algorithms using a suite of datasets which deliberately pose complex DDS challenges for clustering. In order to improve the structure finding and clustering in high-dimensional DDS datasets, projection-based clustering (PBC) is introduced. The coexistence of projection and clustering allows to explore DDS through a topographic map. This enables to estimate, first, if any cluster tendency exists and, second, the estimation of the number of clusters. A comparison showed that PBC is always able to find the correct cluster structure, while the performance of the best of the 32 clustering algorithms varies depending on the dataset." @default.
- W3080491161 created "2020-09-01" @default.
- W3080491161 creator A5018606903 @default.
- W3080491161 creator A5078097779 @default.
- W3080491161 date "2020-08-20" @default.
- W3080491161 modified "2023-10-11" @default.
- W3080491161 title "Using Projection-Based Clustering to Find Distance- and Density-Based Clusters in High-Dimensional Data" @default.
- W3080491161 cites W1270205671 @default.
- W3080491161 cites W1540089290 @default.
- W3080491161 cites W1550159952 @default.
- W3080491161 cites W178343568 @default.
- W3080491161 cites W1885937115 @default.
- W3080491161 cites W1923092445 @default.
- W3080491161 cites W1969557815 @default.
- W3080491161 cites W1976208596 @default.
- W3080491161 cites W1977655121 @default.
- W3080491161 cites W197795972 @default.
- W3080491161 cites W1982792229 @default.
- W3080491161 cites W1990652014 @default.
- W3080491161 cites W199251881 @default.
- W3080491161 cites W1993436046 @default.
- W3080491161 cites W1994041743 @default.
- W3080491161 cites W2001619934 @default.
- W3080491161 cites W2002586964 @default.
- W3080491161 cites W2005317838 @default.
- W3080491161 cites W2007995029 @default.
- W3080491161 cites W2008427435 @default.
- W3080491161 cites W2011832962 @default.
- W3080491161 cites W2016381774 @default.
- W3080491161 cites W2054787086 @default.
- W3080491161 cites W2071128523 @default.
- W3080491161 cites W2077748623 @default.
- W3080491161 cites W2085919530 @default.
- W3080491161 cites W2088323702 @default.
- W3080491161 cites W2088658556 @default.
- W3080491161 cites W2091480648 @default.
- W3080491161 cites W2097919812 @default.
- W3080491161 cites W2107946060 @default.
- W3080491161 cites W2133098435 @default.
- W3080491161 cites W2134383396 @default.
- W3080491161 cites W2137540340 @default.
- W3080491161 cites W2148728150 @default.
- W3080491161 cites W2158485828 @default.
- W3080491161 cites W2165232124 @default.
- W3080491161 cites W2165835468 @default.
- W3080491161 cites W2166322089 @default.
- W3080491161 cites W2169528473 @default.
- W3080491161 cites W2188644105 @default.
- W3080491161 cites W2212737779 @default.
- W3080491161 cites W2234763457 @default.
- W3080491161 cites W2248144625 @default.
- W3080491161 cites W2294798173 @default.
- W3080491161 cites W2312890204 @default.
- W3080491161 cites W2344177848 @default.
- W3080491161 cites W2415715393 @default.
- W3080491161 cites W2520450246 @default.
- W3080491161 cites W2562415598 @default.
- W3080491161 cites W2888523397 @default.
- W3080491161 cites W2968048819 @default.
- W3080491161 cites W2979473749 @default.
- W3080491161 cites W2980548992 @default.
- W3080491161 cites W3003752967 @default.
- W3080491161 cites W3017433385 @default.
- W3080491161 cites W365273601 @default.
- W3080491161 cites W4213007602 @default.
- W3080491161 cites W4213245259 @default.
- W3080491161 cites W4235169531 @default.
- W3080491161 cites W4244268470 @default.
- W3080491161 cites W4254311734 @default.
- W3080491161 cites W4292477917 @default.
- W3080491161 cites W4294141750 @default.
- W3080491161 cites W4298236029 @default.
- W3080491161 cites W658480157 @default.
- W3080491161 doi "https://doi.org/10.1007/s00357-020-09373-2" @default.
- W3080491161 hasPublicationYear "2020" @default.
- W3080491161 type Work @default.
- W3080491161 sameAs 3080491161 @default.
- W3080491161 citedByCount "25" @default.
- W3080491161 countsByYear W30804911612020 @default.
- W3080491161 countsByYear W30804911612021 @default.
- W3080491161 countsByYear W30804911612022 @default.
- W3080491161 countsByYear W30804911612023 @default.
- W3080491161 crossrefType "journal-article" @default.
- W3080491161 hasAuthorship W3080491161A5018606903 @default.
- W3080491161 hasAuthorship W3080491161A5078097779 @default.
- W3080491161 hasBestOaLocation W30804911611 @default.
- W3080491161 hasConcept C11413529 @default.
- W3080491161 hasConcept C115328559 @default.
- W3080491161 hasConcept C124101348 @default.
- W3080491161 hasConcept C153180895 @default.
- W3080491161 hasConcept C154945302 @default.
- W3080491161 hasConcept C164866538 @default.
- W3080491161 hasConcept C17212007 @default.
- W3080491161 hasConcept C184509293 @default.
- W3080491161 hasConcept C186767784 @default.
- W3080491161 hasConcept C199360897 @default.
- W3080491161 hasConcept C22648726 @default.
- W3080491161 hasConcept C23822008 @default.