Matches in SemOpenAlex for { <https://semopenalex.org/work/W4387607440> ?p ?o ?g. }
Showing items 1 to 79 of
79
with 100 items per page.
- W4387607440 endingPage "326" @default.
- W4387607440 startingPage "320" @default.
- W4387607440 abstract "Word embedding, a distributed representation of natural language based on deep neural networks, has made significant breakthroughs in many natural language processing tasks and has gradually become a hot subject in research and application. Word embedding methods can capture more complex and valuable semantic information than existing methods. However, existing methods of word embedding often rely on large-scale annotation resources, which are often difficult to obtain, especially for resource-poor languages. In response to this problem, researchers have explored different research routes, such as unsupervised learning from untagged data, semi-supervised learning that integrates tagged and untagged data, or crowdsourcing. At the same time, many scholars have proposed to improve the analysis accuracy of target tasks by integrating the annotation resources of different languages and enabling knowledge from foreign languages to be transferred or merged with models. This paper discusses the development and prospects of word embedding." @default.
- W4387607440 created "2023-10-14" @default.
- W4387607440 creator A5086866094 @default.
- W4387607440 date "2023-10-09" @default.
- W4387607440 modified "2023-10-14" @default.
- W4387607440 title "Word Embedding for Cross-lingual Natural Language Analysis" @default.
- W4387607440 cites W2054467888 @default.
- W4387607440 cites W2152311353 @default.
- W4387607440 cites W2250539671 @default.
- W4387607440 cites W2759848268 @default.
- W4387607440 cites W2882319491 @default.
- W4387607440 cites W2956530858 @default.
- W4387607440 cites W3035379020 @default.
- W4387607440 cites W3104723404 @default.
- W4387607440 cites W3184324824 @default.
- W4387607440 cites W947140380 @default.
- W4387607440 doi "https://doi.org/10.54097/hset.v68i.12113" @default.
- W4387607440 hasPublicationYear "2023" @default.
- W4387607440 type Work @default.
- W4387607440 citedByCount "0" @default.
- W4387607440 crossrefType "journal-article" @default.
- W4387607440 hasAuthorship W4387607440A5086866094 @default.
- W4387607440 hasConcept C108583219 @default.
- W4387607440 hasConcept C136764020 @default.
- W4387607440 hasConcept C138885662 @default.
- W4387607440 hasConcept C154945302 @default.
- W4387607440 hasConcept C17744445 @default.
- W4387607440 hasConcept C195324797 @default.
- W4387607440 hasConcept C199539241 @default.
- W4387607440 hasConcept C204321447 @default.
- W4387607440 hasConcept C206345919 @default.
- W4387607440 hasConcept C2776321320 @default.
- W4387607440 hasConcept C2776359362 @default.
- W4387607440 hasConcept C2777462759 @default.
- W4387607440 hasConcept C31258907 @default.
- W4387607440 hasConcept C41008148 @default.
- W4387607440 hasConcept C41608201 @default.
- W4387607440 hasConcept C41895202 @default.
- W4387607440 hasConcept C62230096 @default.
- W4387607440 hasConcept C90805587 @default.
- W4387607440 hasConcept C94625758 @default.
- W4387607440 hasConceptScore W4387607440C108583219 @default.
- W4387607440 hasConceptScore W4387607440C136764020 @default.
- W4387607440 hasConceptScore W4387607440C138885662 @default.
- W4387607440 hasConceptScore W4387607440C154945302 @default.
- W4387607440 hasConceptScore W4387607440C17744445 @default.
- W4387607440 hasConceptScore W4387607440C195324797 @default.
- W4387607440 hasConceptScore W4387607440C199539241 @default.
- W4387607440 hasConceptScore W4387607440C204321447 @default.
- W4387607440 hasConceptScore W4387607440C206345919 @default.
- W4387607440 hasConceptScore W4387607440C2776321320 @default.
- W4387607440 hasConceptScore W4387607440C2776359362 @default.
- W4387607440 hasConceptScore W4387607440C2777462759 @default.
- W4387607440 hasConceptScore W4387607440C31258907 @default.
- W4387607440 hasConceptScore W4387607440C41008148 @default.
- W4387607440 hasConceptScore W4387607440C41608201 @default.
- W4387607440 hasConceptScore W4387607440C41895202 @default.
- W4387607440 hasConceptScore W4387607440C62230096 @default.
- W4387607440 hasConceptScore W4387607440C90805587 @default.
- W4387607440 hasConceptScore W4387607440C94625758 @default.
- W4387607440 hasLocation W43876074401 @default.
- W4387607440 hasOpenAccess W4387607440 @default.
- W4387607440 hasPrimaryLocation W43876074401 @default.
- W4387607440 hasRelatedWork W135177976 @default.
- W4387607440 hasRelatedWork W1503094549 @default.
- W4387607440 hasRelatedWork W2337920774 @default.
- W4387607440 hasRelatedWork W2886410948 @default.
- W4387607440 hasRelatedWork W2911655849 @default.
- W4387607440 hasRelatedWork W3032998312 @default.
- W4387607440 hasRelatedWork W3134737443 @default.
- W4387607440 hasRelatedWork W4286432911 @default.
- W4387607440 hasRelatedWork W4318823662 @default.
- W4387607440 hasRelatedWork W4384486036 @default.
- W4387607440 hasVolume "68" @default.
- W4387607440 isParatext "false" @default.
- W4387607440 isRetracted "false" @default.
- W4387607440 workType "article" @default.