Link prediction in weighted networks: The role of weak ties
By Linyuan Lu, Tao Zhou. 2010
319 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Molecular Biology, Statistical and Nonlinear Physics
View Paper: https://www.semanticscholar.org/paper/b7a096d97ee6a741278294b7053dba810e4ea83f
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Víctor Martínez
- Juan C. Cubero
- F. Berzal
- Tao Zhou
- Linyuan Lu
- Sophie Ahrens
- William L. Hamilton
- Yixin Chen
In Molecular Biology
In Statistical and Nonlinear Physics
- Víctor Martínez
- Juan C. Cubero
- F. Berzal
- Tao Zhou
- Linyuan Lu
- Sophie Ahrens
- Jure Leskovec
- William L. Hamilton
Citations in the corpus
- A Survey of Link Prediction in Complex Networks (2016, methodology): “We propose a custom extended version (see Figure 1) of the taxonomy presented by Lü and Zhou [2011]. These taxonomies classify the previously proposed methods attending to the approach they follow and the amount of information that they take into account.”
- Link Prediction in Complex Networks: A Survey (2010, background): “The former [158] suggested that the links with higher weights are more important in predictingmissing links, while the latter [159] indicated a completely opposite conclusion: the weak links play a more significant role.”