Matches in SemOpenAlex for { <https://semopenalex.org/work/W2992877601> ?p ?o ?g. }
Showing items 1 to 99 of
99
with 100 items per page.
- W2992877601 abstract "Subspace clustering is an unsupervised machine learning task that, as clustering, decomposes a data set into subgroups that are both distinct and compact, and that, in addition, explicitly takes into account the fact that the data subgroups live in different subspaces of the feature space. This paper provides a brief survey of the main approaches that have been proposed to address this task, distinguishing between the two paradigms used in the literature: the first one builds a local similarity matrix to extract more appropriate data subgroups, whereas the second one explicitly identifies the subspaces, so as to dispose of more complete information about the clusters. It then focuses on soft computing approaches, that in particular exploit the framework of the fuzzy set theory to identify both the data subgroups and their associated subspaces." @default.
- W2992877601 created "2019-12-13" @default.
- W2992877601 creator A5075900406 @default.
- W2992877601 date "2019-01-01" @default.
- W2992877601 modified "2023-09-30" @default.
- W2992877601 title "Subspace Clustering and Some Soft Variants" @default.
- W2992877601 cites W1506518385 @default.
- W2992877601 cites W1536340840 @default.
- W2992877601 cites W1539123096 @default.
- W2992877601 cites W1987801991 @default.
- W2992877601 cites W1993962865 @default.
- W2992877601 cites W1997201895 @default.
- W2992877601 cites W2017441234 @default.
- W2992877601 cites W2042035594 @default.
- W2992877601 cites W2065811242 @default.
- W2992877601 cites W2080476941 @default.
- W2992877601 cites W2109863804 @default.
- W2992877601 cites W2112210867 @default.
- W2992877601 cites W2125070513 @default.
- W2992877601 cites W2128917343 @default.
- W2992877601 cites W2132914434 @default.
- W2992877601 cites W2410894298 @default.
- W2992877601 cites W2745361460 @default.
- W2992877601 cites W2811375137 @default.
- W2992877601 cites W2884851420 @default.
- W2992877601 cites W2963764968 @default.
- W2992877601 cites W2964837208 @default.
- W2992877601 cites W3003734944 @default.
- W2992877601 cites W4243967044 @default.
- W2992877601 cites W4250657332 @default.
- W2992877601 doi "https://doi.org/10.1007/978-3-030-35514-2_33" @default.
- W2992877601 hasPublicationYear "2019" @default.
- W2992877601 type Work @default.
- W2992877601 sameAs 2992877601 @default.
- W2992877601 citedByCount "2" @default.
- W2992877601 countsByYear W29928776012020 @default.
- W2992877601 crossrefType "book-chapter" @default.
- W2992877601 hasAuthorship W2992877601A5075900406 @default.
- W2992877601 hasConcept C103278499 @default.
- W2992877601 hasConcept C115961682 @default.
- W2992877601 hasConcept C12362212 @default.
- W2992877601 hasConcept C124101348 @default.
- W2992877601 hasConcept C153180895 @default.
- W2992877601 hasConcept C154945302 @default.
- W2992877601 hasConcept C162324750 @default.
- W2992877601 hasConcept C165696696 @default.
- W2992877601 hasConcept C17212007 @default.
- W2992877601 hasConcept C177264268 @default.
- W2992877601 hasConcept C187736073 @default.
- W2992877601 hasConcept C199360897 @default.
- W2992877601 hasConcept C2524010 @default.
- W2992877601 hasConcept C2780451532 @default.
- W2992877601 hasConcept C32834561 @default.
- W2992877601 hasConcept C33923547 @default.
- W2992877601 hasConcept C38652104 @default.
- W2992877601 hasConcept C41008148 @default.
- W2992877601 hasConcept C42011625 @default.
- W2992877601 hasConcept C58166 @default.
- W2992877601 hasConcept C73555534 @default.
- W2992877601 hasConcept C83665646 @default.
- W2992877601 hasConceptScore W2992877601C103278499 @default.
- W2992877601 hasConceptScore W2992877601C115961682 @default.
- W2992877601 hasConceptScore W2992877601C12362212 @default.
- W2992877601 hasConceptScore W2992877601C124101348 @default.
- W2992877601 hasConceptScore W2992877601C153180895 @default.
- W2992877601 hasConceptScore W2992877601C154945302 @default.
- W2992877601 hasConceptScore W2992877601C162324750 @default.
- W2992877601 hasConceptScore W2992877601C165696696 @default.
- W2992877601 hasConceptScore W2992877601C17212007 @default.
- W2992877601 hasConceptScore W2992877601C177264268 @default.
- W2992877601 hasConceptScore W2992877601C187736073 @default.
- W2992877601 hasConceptScore W2992877601C199360897 @default.
- W2992877601 hasConceptScore W2992877601C2524010 @default.
- W2992877601 hasConceptScore W2992877601C2780451532 @default.
- W2992877601 hasConceptScore W2992877601C32834561 @default.
- W2992877601 hasConceptScore W2992877601C33923547 @default.
- W2992877601 hasConceptScore W2992877601C38652104 @default.
- W2992877601 hasConceptScore W2992877601C41008148 @default.
- W2992877601 hasConceptScore W2992877601C42011625 @default.
- W2992877601 hasConceptScore W2992877601C58166 @default.
- W2992877601 hasConceptScore W2992877601C73555534 @default.
- W2992877601 hasConceptScore W2992877601C83665646 @default.
- W2992877601 hasLocation W29928776011 @default.
- W2992877601 hasOpenAccess W2992877601 @default.
- W2992877601 hasPrimaryLocation W29928776011 @default.
- W2992877601 hasRelatedWork W1508520931 @default.
- W2992877601 hasRelatedWork W1563099561 @default.
- W2992877601 hasRelatedWork W1970423070 @default.
- W2992877601 hasRelatedWork W2053673812 @default.
- W2992877601 hasRelatedWork W2070651420 @default.
- W2992877601 hasRelatedWork W2139372249 @default.
- W2992877601 hasRelatedWork W2370210292 @default.
- W2992877601 hasRelatedWork W2993997359 @default.
- W2992877601 hasRelatedWork W919364087 @default.
- W2992877601 hasRelatedWork W3143668392 @default.
- W2992877601 isParatext "false" @default.
- W2992877601 isRetracted "false" @default.
- W2992877601 magId "2992877601" @default.
- W2992877601 workType "book-chapter" @default.