A novel transfer learning model for traditional herbal medicine prescription generation from unstructured resources and knowledge.

Traditional Chinese medicine (TCM) is an essential part of the world's traditional medicine. However, there are still many issues in the promotion and development of TCM, such as a lot of unique TCM treatments are taught only between the master and an apprentice in practice, it takes dozens of years for a TCM practitioner to master them and the complicated TCM treatment principles. Intelligent TCM models, as a promising method, can overcome these issues.

TCMNER and PubMed: A Novel Chinese Character-Level-Based Model and a Dataset for TCM Named Entity Recognition.

Intelligent traditional Chinese medicine (TCM) has become a popular research field by means of prospering of deep learning technology. Important achievements have been made in such representative tasks as automatic diagnosis of TCM syndromes and diseases and generation of TCM herbal prescriptions. However, one unavoidable issue that still hinders its progress is the lack of labeled samples, i.

Dynamics of calling activity to toll-free numbers in China.

The quantitative understanding of human behavior is a key issue in modern science. Recently, inhomogeneous human activities have been described by bursts (consecutive activities separated by long periods of inactivity) and characterized by fat-tailed inter-event time (interval between two activities) distributions. However, the dynamics between number of activities and activity duration are still unclear.

Factors influencing message dissemination through social media.

Online social networks strongly impact our daily lives. An internet user (a "Netizen") wants messages to be efficiently disseminated. The susceptible-infected-recovered (SIR) dissemination model is the traditional tool for exploring the spreading mechanism of information diffusion.