MCRWR: a new method to measure the similarity of documents based on semantic network

• Published in: BMC bioinformatics Vol. 23; no. 1; pp. 56 - 17
• Main Authors: Pan, Xianwei, Huang, Peng, Li, Shan, Cui, Lei
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 01.02.2022; BioMed Central; BMC
• Subjects: Algorithms; Analysis; Boolean algebra; Citations; Cocitation; Documents; Finite element method; Genomes; Medical Subject Headings; Methods; Network analysis; PubMed; Random walk; Random walk with restart algorithm; Semantic networks; Semantic relations; Semantic similarity network; Semantic Web; Semantics; Similarity; Similarity judgment; Subject headings; China; Semantic similarity network; Random walk with restart algorithm; Medical subject headings; Network analysis

Besides Boolean retrieval with medical subject headings (MeSH), PubMed provides users with an alternative way called "Related Articles" to access and collect relevant documents based on semantic similarity. To explore the functionality more efficiently and more accurately, we proposed an i...