IMF: Interpretable Multi-Hop Forecasting on Temporal Knowledge Graphs
IMF: Interpretable Multi-Hop Forecasting on Temporal Knowledge Graphs
About this item
Full title
Author / Creator
Du, Zhenyu , Qu, Lingzhi , Liang, Zongwei , Huang, Keju , Cui, Lin and Gao, Zhiyang
Publisher
Switzerland: MDPI AG
Journal title
Language
English
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Publication information
Publisher
Switzerland: MDPI AG
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Scope and Contents
Contents
Temporal knowledge graphs (KGs) have recently attracted increasing attention. The temporal KG forecasting task, which plays a crucial role in such applications as event prediction, predicts future links based on historical facts. However, current studies pay scant attention to the following two aspects. First, the interpretability of current models...
Alternative Titles
Full title
IMF: Interpretable Multi-Hop Forecasting on Temporal Knowledge Graphs
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Author / Creator
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Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_d540ce95a0124dd2b20ed937faab05d8
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_d540ce95a0124dd2b20ed937faab05d8
Other Identifiers
ISSN
1099-4300
E-ISSN
1099-4300
DOI
10.3390/e25040666
