Technology feature fusion prediction method based on multidimensional information extraction and deep neural networks.
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| Title: | Technology feature fusion prediction method based on multidimensional information extraction and deep neural networks. |
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| Authors: | Zhang, Hong1,2, 710149930@qq.com, Chen, Yanchun1, 376146485@qq.com |
| Source: | Knowledge & Information Systems; Oct2025, Vol. 67 Issue 10, p9051-9084, 34p |
| 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: 188684101 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Technology feature fusion prediction method based on multidimensional information extraction and deep neural networks. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AU" term="%22Zhang%2C+Hong%22">Zhang, Hong</searchLink><relatesTo>1,2</relatesTo>, <i>710149930@qq.com</i><br /><searchLink fieldCode="AU" term="%22Chen%2C+Yanchun%22">Chen, Yanchun</searchLink><relatesTo>1</relatesTo>, <i>376146485@qq.com</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Knowledge+%26+Information+Systems%22">Knowledge & Information Systems</searchLink>; Oct2025, Vol. 67 Issue 10, p9051-9084, 34p |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=188684101 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s10115-025-02496-1 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 34 StartPage: 9051 Titles: – TitleFull: Technology feature fusion prediction method based on multidimensional information extraction and deep neural networks. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Zhang, Hong – PersonEntity: Name: NameFull: Chen, Yanchun IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 10 Text: Oct2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 02191377 Numbering: – Type: volume Value: 67 – Type: issue Value: 10 Titles: – TitleFull: Knowledge & Information Systems Type: main |
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