Emotion detection in text using a legendre memory unit based deep learning framework.
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| Title: | Emotion detection in text using a legendre memory unit based deep learning framework. |
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| Authors: | Khan, Abrar1, abrarkhan@nitp.ac.in, Kumar, Prabhat1, prabhat@nitp.ac.in |
| Source: | Multimedia Tools & Applications; Oct2025, Vol. 84 Issue 35, p44017-44032, 16p |
| Database: | Applied Science & Technology Source |
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| FullText | Links: – Type: pdflink Text: Availability: 1 |
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| Header | DbId: aci DbLabel: Applied Science & Technology Source An: 188906146 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Emotion detection in text using a legendre memory unit based deep learning framework. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AU" term="%22Khan%2C+Abrar%22">Khan, Abrar</searchLink><relatesTo>1</relatesTo>, <i>abrarkhan@nitp.ac.in</i><br /><searchLink fieldCode="AU" term="%22Kumar%2C+Prabhat%22">Kumar, Prabhat</searchLink><relatesTo>1</relatesTo>, <i>prabhat@nitp.ac.in</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Multimedia+Tools+%26+Applications%22">Multimedia Tools & Applications</searchLink>; Oct2025, Vol. 84 Issue 35, p44017-44032, 16p |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=188906146 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s11042-025-20891-2 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 16 StartPage: 44017 Titles: – TitleFull: Emotion detection in text using a legendre memory unit based deep learning framework. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Khan, Abrar – PersonEntity: Name: NameFull: Kumar, Prabhat IsPartOfRelationships: – BibEntity: Dates: – D: 28 M: 10 Text: Oct2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 13807501 Numbering: – Type: volume Value: 84 – Type: issue Value: 35 Titles: – TitleFull: Multimedia Tools & Applications Type: main |
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