Matches in SemOpenAlex for { <https://semopenalex.org/work/W2887978789> ?p ?o ?g. }
Showing items 1 to 80 of
80
with 100 items per page.
- W2887978789 endingPage "162" @default.
- W2887978789 startingPage "152" @default.
- W2887978789 abstract "Labeled Latent Dirichlet Allocation (LLDA) is an extension of the standard unsupervised Latent Dirichlet Allocation (LDA) algorithm, to address multi-label learning tasks. Previous work has shown it to perform en par with other state-of-the-art multi-label methods. Nonetheless, with increasing number of labels LLDA encounters scalability issues. In this work, we introduce Subset LLDA, a topic model that extends the standard LLDA algorithm, that not only can efficiently scale up to problems with hundreds of thousands of labels but also improves over the LLDA state-of-the-art in terms of prediction accuracy. We conduct experiments on eight data sets, with labels ranging from hundreds to hundreds of thousands, comparing our proposed algorithm with the other LLDA algorithms (Prior–LDA, Dep–LDA), as well as the state-of-the-art in extreme multi-label classification. The results show a steady advantage of our method over the other LLDA algorithms and competitive results compared to the extreme multi-label classification algorithms." @default.
- W2887978789 created "2018-08-22" @default.
- W2887978789 creator A5026561247 @default.
- W2887978789 creator A5061499531 @default.
- W2887978789 date "2018-01-01" @default.
- W2887978789 modified "2023-10-12" @default.
- W2887978789 title "Subset Labeled LDA: A Topic Model for Extreme Multi-label Classification" @default.
- W2887978789 cites W1524416683 @default.
- W2887978789 cites W1969486090 @default.
- W2887978789 cites W1979495886 @default.
- W2887978789 cites W1981208470 @default.
- W2887978789 cites W2001082470 @default.
- W2887978789 cites W2068074736 @default.
- W2887978789 cites W2074909580 @default.
- W2887978789 cites W2146241755 @default.
- W2887978789 cites W2362855512 @default.
- W2887978789 cites W2963491860 @default.
- W2887978789 doi "https://doi.org/10.1007/978-3-319-98539-8_12" @default.
- W2887978789 hasPublicationYear "2018" @default.
- W2887978789 type Work @default.
- W2887978789 sameAs 2887978789 @default.
- W2887978789 citedByCount "3" @default.
- W2887978789 countsByYear W28879787892020 @default.
- W2887978789 countsByYear W28879787892021 @default.
- W2887978789 crossrefType "book-chapter" @default.
- W2887978789 hasAuthorship W2887978789A5026561247 @default.
- W2887978789 hasAuthorship W2887978789A5061499531 @default.
- W2887978789 hasConcept C119857082 @default.
- W2887978789 hasConcept C121332964 @default.
- W2887978789 hasConcept C124101348 @default.
- W2887978789 hasConcept C134306372 @default.
- W2887978789 hasConcept C153180895 @default.
- W2887978789 hasConcept C154945302 @default.
- W2887978789 hasConcept C169214877 @default.
- W2887978789 hasConcept C171686336 @default.
- W2887978789 hasConcept C182310444 @default.
- W2887978789 hasConcept C2776482837 @default.
- W2887978789 hasConcept C2778755073 @default.
- W2887978789 hasConcept C33923547 @default.
- W2887978789 hasConcept C41008148 @default.
- W2887978789 hasConcept C48044578 @default.
- W2887978789 hasConcept C500882744 @default.
- W2887978789 hasConcept C62520636 @default.
- W2887978789 hasConcept C77088390 @default.
- W2887978789 hasConceptScore W2887978789C119857082 @default.
- W2887978789 hasConceptScore W2887978789C121332964 @default.
- W2887978789 hasConceptScore W2887978789C124101348 @default.
- W2887978789 hasConceptScore W2887978789C134306372 @default.
- W2887978789 hasConceptScore W2887978789C153180895 @default.
- W2887978789 hasConceptScore W2887978789C154945302 @default.
- W2887978789 hasConceptScore W2887978789C169214877 @default.
- W2887978789 hasConceptScore W2887978789C171686336 @default.
- W2887978789 hasConceptScore W2887978789C182310444 @default.
- W2887978789 hasConceptScore W2887978789C2776482837 @default.
- W2887978789 hasConceptScore W2887978789C2778755073 @default.
- W2887978789 hasConceptScore W2887978789C33923547 @default.
- W2887978789 hasConceptScore W2887978789C41008148 @default.
- W2887978789 hasConceptScore W2887978789C48044578 @default.
- W2887978789 hasConceptScore W2887978789C500882744 @default.
- W2887978789 hasConceptScore W2887978789C62520636 @default.
- W2887978789 hasConceptScore W2887978789C77088390 @default.
- W2887978789 hasLocation W28879787891 @default.
- W2887978789 hasOpenAccess W2887978789 @default.
- W2887978789 hasPrimaryLocation W28879787891 @default.
- W2887978789 hasRelatedWork W2207653751 @default.
- W2887978789 hasRelatedWork W2769501189 @default.
- W2887978789 hasRelatedWork W2796920963 @default.
- W2887978789 hasRelatedWork W2888805565 @default.
- W2887978789 hasRelatedWork W2891616219 @default.
- W2887978789 hasRelatedWork W3005513013 @default.
- W2887978789 hasRelatedWork W3204672119 @default.
- W2887978789 hasRelatedWork W4312773271 @default.
- W2887978789 hasRelatedWork W4315588616 @default.
- W2887978789 hasRelatedWork W2611137333 @default.
- W2887978789 isParatext "false" @default.
- W2887978789 isRetracted "false" @default.
- W2887978789 magId "2887978789" @default.
- W2887978789 workType "book-chapter" @default.