基于张量 CP 分解的不完整数据自适应图特征选择.
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| Title: | 基于张量 CP 分解的不完整数据自适应图特征选择. |
|---|---|
| Alternate Title: | Adaptive Graph Feature Selection Based on Tensor CP Decomposition for Incomplete Data. |
| Authors: | 刘家徐1, 宋 燕1 sonya@usst.edu.cn, 窦 军2, 张亚萌1 |
| Source: | Electronic Science & Technology. 2026, Vol. 39 Issue 6, p1-11. 11p. |
| Database: | Academic Search Ultimate |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: asn DbLabel: Academic Search Ultimate An: 194649200 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: 基于张量 CP 分解的不完整数据自适应图特征选择. – Name: TitleAlt Label: Alternate Title Group: TiAlt Data: Adaptive Graph Feature Selection Based on Tensor CP Decomposition for Incomplete Data. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22刘家徐%22">刘家徐</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22宋+燕%22">宋 燕</searchLink><relatesTo>1</relatesTo><i> sonya@usst.edu.cn</i><br /><searchLink fieldCode="AR" term="%22窦+军%22">窦 军</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22张亚萌%22">张亚萌</searchLink><relatesTo>1</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Electronic+Science+%26+Technology%22">Electronic Science & Technology</searchLink>. 2026, Vol. 39 Issue 6, p1-11. 11p. |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=194649200 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.16180/j.cnki.issn1007-7820.2026.06.001 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 11 StartPage: 1 Titles: – TitleFull: 基于张量 CP 分解的不完整数据自适应图特征选择. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: 刘家徐 – PersonEntity: Name: NameFull: 宋 燕 – PersonEntity: Name: NameFull: 窦 军 – PersonEntity: Name: NameFull: 张亚萌 IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 06 Text: 2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 10077820 Numbering: – Type: volume Value: 39 – Type: issue Value: 6 Titles: – TitleFull: Electronic Science & Technology Type: main |
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