Optimizations for Computing Relatedness in Biomedical Heterogeneous Information Networks: SemNet 2.0

Optimizations for Computing Relatedness in Biomedical Heterogeneous Information Networks: SemNet 2.0

Literature-based discovery (LBD) summarizes information and generates insight from large text corpuses. The SemNet framework utilizes a large heterogeneous information network or “knowledge graph” of nodes and edges to compute relatedness and rank concepts pertinent to a user-specified target. SemNe...

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Bibliographic Details
Main Authors: Anna Kirkpatrick, Chidozie Onyeze, David Kartchner, Stephen Allegri, Davi Nakajima An, Kevin McCoy, Evie Davalbhakta, Cassie S. Mitchell
Format: Article
Language:English
Published: MDPI AG 2022-03-01
Series:Big Data and Cognitive Computing
Subjects:
HeteSim
ULARA
SemNet
Alzheimer’s disease
natural language processing
machine learning
Online Access:https://www.mdpi.com/2504-2289/6/1/27

Internet

https://www.mdpi.com/2504-2289/6/1/27

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