Locality-aware tail node embeddings on homogeneous and heterogeneous networks

• Main Authors: LIU, Zemin, FANG, Yuan, ZHANG, Wentao, ZHANG, Xinming, HOI, Steven C. H.
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2023
• Subjects: Adaptation models; Encyclopedias; Heterogeneous networks; homogeneous and heterogeneous networks; locality-aware; Meta-learning; Metalearning; Representation learning; Tail; tail node embeddings; Task analysis; Artificial Intelligence and Robotics; Databases and Information Systems
• Online Access: https://ink.library.smu.edu.sg/sis_research/8254; https://ink.library.smu.edu.sg/context/sis_research/article/9257/viewcontent/Locality_Aware_Tail_Node_av.pdf
• Institution: Singapore Management University

While the state-of-the-art network embedding approaches often learn high-quality embeddings for high-degree nodes with abundant structural connectivity, the quality of the embeddings for low-degree or nodes is often suboptimal due to their limited structural connectivity. While many real-world netwo...