A Method of Biomedical Knowledge Discovery by Literature Mining Based on SPO Predications: A Case Study of Induced Pluripotent Stem Cells

A large amount of valuable knowledge is hidden in the vast biomedical literatures, publications, and online contents. In order to identify the previously unknown biomedical knowledge from these resources, we propose a new method of knowledge discovery based on SPO predications, which constructs a three-level SPO-semantic relation network in the considered area. We carry out the experiments in the area of induced pluripotent stem cells, and the experimental results indicate that our proposed method can significantly discover the potential biomedical knowledge in this area, and the performance analysis of this method sheds lights on the ways to further improvements

Mining Hot Research Topics based on Complex Network Analysis - A Case Study on Regenerative Medicine

In order to mine the hot research topics of a certain field, we propose a hypervolume-based selection algorithm based on the complex network analysis, which employs a hypervolume indicator to select the hot research topics from the network in the considered field. We carry out the experiments in the field of regenerative medicine, and the experimental results indicate that our proposed method can effectively find the hot research topics in this field. The performance analysis sheds lights on the ways to further improvements. </span