Spatio-Temporal Information Extraction and Geoparsing for Public Chinese Resumes

As an important carrier of individual information, the resume is data source for studying spatio-temporal evolutionary characteristics and group behaviors. This study focuses on information extraction geoparsing from resumes to provide basic technical support research based text. Most current studies text are oriented toward recruitment work, such as automated extraction, classification, recommendation resumes. These ignore behaviors implied in Therefore, this takes public teachers key universities China data, proposes a set solutions electronic figures, designs spatial entity method, which can effectively extract spatially locate To verify effectiveness proposed models BiLSTM-CRF, BERT-CRF, BERT-BiLSTM-CRF selected conduct comparative experiments, method verified. The experimental results show that precision named recognition task 96.23% designed 97.91%.