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SumGNN: multi-typed drug interaction prediction via efficient knowledge graph summarization
Motivation Thanks to the increasing availability of drug–drug interactions (DDI) datasets and
large biomedical knowledge graphs (KGs), accurate detection of adverse DDI using …
large biomedical knowledge graphs (KGs), accurate detection of adverse DDI using …
Enhancing taxonomy completion with concept generation via fusing relational representations
Automatic construction of a taxonomy supports many applications in e-commerce, web
search, and question answering. Existing taxonomy expansion or completion methods …
search, and question answering. Existing taxonomy expansion or completion methods …
Taxocom: Topic taxonomy completion with hierarchical discovery of novel topic clusters
Topic taxonomies, which represent the latent topic (or category) structure of document
collections, provide valuable knowledge of contents in many applications such as web …
collections, provide valuable knowledge of contents in many applications such as web …
[PDF][PDF] TaxoPrompt: A Prompt-based Generation Method with Taxonomic Context for Self-Supervised Taxonomy Expansion.
H Xu, Y Chen, Z Liu, Y Wen, X Yuan - IJCAI, 2022 - ijcai.org
Taxonomies are hierarchical classifications widely exploited to facilitate downstream natural
language processing tasks. The taxonomy expansion task aims to incorporate emergent …
language processing tasks. The taxonomy expansion task aims to incorporate emergent …
A review on knowledge graphs for healthcare: Resources, applications, and promises
Healthcare knowledge graphs (HKGs) are valuable tools for organizing biomedical concepts
and their relationships with interpretable structures. The recent advent of large language …
and their relationships with interpretable structures. The recent advent of large language …