Representation Learning for Measuring Entity Relatedness with Rich Information

By Yu Zhao, Zhiyuan Liu, Maosong Sun. 2015

38 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Hongyun Cai
2. Vincent Wenchen Zheng
3. Kevin Chen-Chuan Chang
4. Masanao Ochi
5. Yuko Nakashio
6. Ichiro Sakata
7. Junichiro Mori
8. Matthew Ruttley

Citations in the corpus

• A Comprehensive Survey of Graph Embedding: Problems, Techniques, and Applications (2017, background): “nodes of interest to a given node based on certain criteria such as similarity [3], [16], [43], [45], [47], [106].”
• Geospatial Area Embedding Based on the Movement Purpose Hypothesis Using Large-Scale Mobility Data from Smart Card (2016, methodology): “These network-embedding methods are useful in many tasks such as visualization, node classification, and link prediction [23].”