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TAGA: Text-Attributed Graph Self-Supervised Learning by Synergizing Graph and Text Mutual Transformations

(2025)10.1145/3746252.3761357Source: DataRank Database

TAGA: Text-Attributed Graph Self-Supervised Learning by Synergizing Graph and Text Mutual Transformations is a research paper (2025). On theSindex it has a DataRank of 0. It has been cited 1 time.

N/A

0DataRank · unranked

Scored on demand from live citation data

Open Access1 citations

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (2 grants)Impact (FWCI 1.62)OA: goldTopics (11)IDs (PubMed, OpenAlex)

FAIR Checklist

Context only (not used in score)

Findable (1/2)

Has DOI

Accessible (1/2)

Open Access

Interoperable (0/2)

Reusable (0/3)

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Authors (5)

Yuntong Hu ORCID,Bo Pan ORCID,Chen Ling ORCID,Liang Zhao ORCID,Zheng Zhang ORCID

Live enrichment

PubMed:19910364 OpenAlex:https://openalex.org/W4416017568

NSF (National Science Foundation)

Grant: 2007716, 2007976, 1942594, 1907805

NIH (National Institutes of Health)

Grant: R01AG089806

FWCI

1.62

Citation Percentile

0.9%

Citation Trend

2025

goldLicense: cc-by

https://doi.org/10.1145/3746252.3761357

publisherhttps://dl.acm.org/doi/abs/10.1145/3746252.3761357

publisherhttps://dl.acm.org/doi/pdf/10.1145/3746252.3761357

Fields of Study

Advanced Graph Neural NetworksTopic ModelingGraph Theory and Algorithms

Keywords

GraphFeature learningLimitingRepresentation (politics)Node (physics)Natural language understandingLabeled dataKnowledge graph