Automatic labeling and extraction of terms in natural language processing in acupuncture clinical literature / 中国针灸

The paper analyzes the specificity of term recognition in acupuncture clinical literature and compares the advantages and disadvantages of three named entity recognition (NER) methods adopted in the field of traditional Chinese medicine. It is believed that the bi-directional long short-term memory networks-conditional random fields (Bi LSTM-CRF) may communicate the context information and complete NER by using less feature rules. This model is suitable for term recognition in acupuncture clinical literature. Based on this model, it is proposed that the process of term recognition in acupuncture clinical literature should include 4 aspects, i.e. literature pretreatment, sequence labeling, model training and effect evaluation, which provides an approach to the terminological structurization in acupuncture clinical literature.

On the possibility of using reaction time to study false memories

Research on false memories has extensively used the recognition and recollection of lists of semantically associated words, called the Deese-Roediger-McDermott (DRM) paradigm. In the DRM procedure, the measure of accuracy/errors is usually the main dependent variable. In this paper we review research that integrated reaction time measures into the DRM paradigm and discuss the future contributions of measures of reaction time to the understanding of false memories.