Matches in SemOpenAlex for { <https://semopenalex.org/work/W3007882656> ?p ?o ?g. }
Showing items 1 to 83 of
83
with 100 items per page.
- W3007882656 endingPage "86" @default.
- W3007882656 startingPage "74" @default.
- W3007882656 abstract "Arabic text categorization is an important task in text mining particularly with the fast-increasing quantity of the Arabic online data. Deep neural network models have shown promising performance and indicated great data modeling capacities in managing large and substantial datasets. This article investigates convolution neural networks (CNNs), long short-term memory (LSTM) and their combination for Arabic text categorization. This work additionally handles the morphological variety of Arabic words by exploring the word embeddings model using position weights and subword information. To guarantee the nearest vector representations for connected words, this article adopts a strategy for refining Arabic vector space representations using semantic information embedded in lexical resources. Several experiments utilizing different architectures have been conducted on the OSAC dataset. The obtained results show the effectiveness of CNN-LSTM without and with retrofitting for Arabic text categorization in comparison with major competing methods." @default.
- W3007882656 created "2020-03-06" @default.
- W3007882656 creator A5004210985 @default.
- W3007882656 creator A5048941252 @default.
- W3007882656 creator A5084532237 @default.
- W3007882656 date "2020-04-01" @default.
- W3007882656 modified "2023-10-02" @default.
- W3007882656 title "Deep Neural Models and Retrofitting for Arabic Text Categorization" @default.
- W3007882656 cites W1503259811 @default.
- W3007882656 cites W1832693441 @default.
- W3007882656 cites W2000867453 @default.
- W3007882656 cites W2064675550 @default.
- W3007882656 cites W2083525772 @default.
- W3007882656 cites W2087259979 @default.
- W3007882656 cites W2113828392 @default.
- W3007882656 cites W2120615054 @default.
- W3007882656 cites W2141734078 @default.
- W3007882656 cites W2251137535 @default.
- W3007882656 cites W2265846598 @default.
- W3007882656 cites W2493916176 @default.
- W3007882656 cites W2530979053 @default.
- W3007882656 cites W2540218936 @default.
- W3007882656 cites W2832139998 @default.
- W3007882656 cites W2897065501 @default.
- W3007882656 cites W2944085222 @default.
- W3007882656 doi "https://doi.org/10.4018/ijiit.2020040104" @default.
- W3007882656 hasPublicationYear "2020" @default.
- W3007882656 type Work @default.
- W3007882656 sameAs 3007882656 @default.
- W3007882656 citedByCount "12" @default.
- W3007882656 countsByYear W30078826562020 @default.
- W3007882656 countsByYear W30078826562021 @default.
- W3007882656 countsByYear W30078826562022 @default.
- W3007882656 countsByYear W30078826562023 @default.
- W3007882656 crossrefType "journal-article" @default.
- W3007882656 hasAuthorship W3007882656A5004210985 @default.
- W3007882656 hasAuthorship W3007882656A5048941252 @default.
- W3007882656 hasAuthorship W3007882656A5084532237 @default.
- W3007882656 hasConcept C12267149 @default.
- W3007882656 hasConcept C136197465 @default.
- W3007882656 hasConcept C138885662 @default.
- W3007882656 hasConcept C154945302 @default.
- W3007882656 hasConcept C204321447 @default.
- W3007882656 hasConcept C41008148 @default.
- W3007882656 hasConcept C41895202 @default.
- W3007882656 hasConcept C50644808 @default.
- W3007882656 hasConcept C81363708 @default.
- W3007882656 hasConcept C90805587 @default.
- W3007882656 hasConcept C94124525 @default.
- W3007882656 hasConcept C96455323 @default.
- W3007882656 hasConceptScore W3007882656C12267149 @default.
- W3007882656 hasConceptScore W3007882656C136197465 @default.
- W3007882656 hasConceptScore W3007882656C138885662 @default.
- W3007882656 hasConceptScore W3007882656C154945302 @default.
- W3007882656 hasConceptScore W3007882656C204321447 @default.
- W3007882656 hasConceptScore W3007882656C41008148 @default.
- W3007882656 hasConceptScore W3007882656C41895202 @default.
- W3007882656 hasConceptScore W3007882656C50644808 @default.
- W3007882656 hasConceptScore W3007882656C81363708 @default.
- W3007882656 hasConceptScore W3007882656C90805587 @default.
- W3007882656 hasConceptScore W3007882656C94124525 @default.
- W3007882656 hasConceptScore W3007882656C96455323 @default.
- W3007882656 hasIssue "2" @default.
- W3007882656 hasLocation W30078826561 @default.
- W3007882656 hasOpenAccess W3007882656 @default.
- W3007882656 hasPrimaryLocation W30078826561 @default.
- W3007882656 hasRelatedWork W2040397200 @default.
- W3007882656 hasRelatedWork W2048978997 @default.
- W3007882656 hasRelatedWork W2124397784 @default.
- W3007882656 hasRelatedWork W2355927362 @default.
- W3007882656 hasRelatedWork W2365213443 @default.
- W3007882656 hasRelatedWork W2748454020 @default.
- W3007882656 hasRelatedWork W2996933976 @default.
- W3007882656 hasRelatedWork W4301311969 @default.
- W3007882656 hasRelatedWork W4384103574 @default.
- W3007882656 hasRelatedWork W2188432624 @default.
- W3007882656 hasVolume "16" @default.
- W3007882656 isParatext "false" @default.
- W3007882656 isRetracted "false" @default.
- W3007882656 magId "3007882656" @default.
- W3007882656 workType "article" @default.