Combining entity co-occurrence with specialized word embeddings to measure entity relation in Alzheimer's disease.

Journal: BMC medical informatics and decision making
Published Date:

Abstract

BACKGROUND: Extracting useful information from biomedical literature plays an important role in the development of modern medicine. In natural language processing, there have been rigorous attempts to find meaningful relationships between entities automatically by co-occurrence-based methods. It has been increasingly important to understand whether relationships exist, and if so how strong, between any two entities extracted from a large number of texts. One of the defining methods is to measure semantic similarity and relatedness between two entities.

Authors

  • Go Eun Heo
    Department of Library and Information Science, Yonsei University, 50 Yonsei-ro Seodaemun-gu, Seoul, 03722, Republic of Korea.
  • Qing Xie
    Department of Infectious Disease, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
  • Min Song
    Library and Information Science, Yonsei University, Seoul, South Korea.
  • Jeong-Hoon Lee