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Link Prediction with Hypergraphs via Network Embedding

Link Prediction with Hypergraphs via Network Embedding

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_2b17d5de4b9648a1a32b9dd1eb537f8d

Link Prediction with Hypergraphs via Network Embedding

About this item

Full title

Link Prediction with Hypergraphs via Network Embedding

Publisher

Basel: MDPI AG

Journal title

Applied sciences, 2023-01, Vol.13 (1), p.523

Language

English

Formats

Publication information

Publisher

Basel: MDPI AG

More information

Scope and Contents

Contents

Network embedding is a promising field and is important for various network analysis tasks, such as link prediction, node classification, community detection and others. Most research studies on link prediction focus on simple networks and pay little attention to hypergraphs that provide a natural way to represent complex higher-order relationships...

Alternative Titles

Full title

Link Prediction with Hypergraphs via Network Embedding

Authors, Artists and Contributors

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_doaj_primary_oai_doaj_org_article_2b17d5de4b9648a1a32b9dd1eb537f8d

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_2b17d5de4b9648a1a32b9dd1eb537f8d

Other Identifiers

ISSN

2076-3417

E-ISSN

2076-3417

DOI

10.3390/app13010523

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