Transfer Hawkes processes with content information

• Main Authors: Li, Tianbo, Wei, Pengfei, Ke, Yiping
• Other Authors: School of Computer Science and Engineering
• Format: Conference or Workshop Item
• Language: English
• Published: 2020
• Subjects: Engineering::Computer science and engineering::Computer applications; Hawkes Processes; Transfer Learning
• Online Access: https://hdl.handle.net/10356/142999
• Institution: Nanyang Technological University

Hawkes processes are widely used for modeling event cascades. However, content and cross-domain information which is also instrumental in modeling is usually neglected. In this paper, we propose a novel model called transfer Hybrid Least Square for Hawkes (trHLSH) that incorporates Hawkes processes with content and cross-domain information. We also present the effective learning algorithm for the model. Evaluation on both synthetic and real-world datasets demonstrates that the proposed model can jointly learn knowledge from temporal, content and cross-domain information, and has better performance in terms of network recovery and prediction.