Research on Entity Recognition and Alignment Methods in Knowledge Graph Construction of Multi-source Tourism Data

In recent years, the tourism field related websites are increasing day by day, the network has produced massive tourist generation data. Based on the semi-structured data of scenic spots, hotels and caterings on tourist websites and the travel notes published by tourists, this paper constructed the tourism knowledge graph. The extraction of entities from travel notes was faced with the problems of named entity recognition and entity alignment. In order to improve the accuracy of extracting entities from travel notes, in this paper, the named entity recognition model based on BiLSTM-CRF and the entity alignment model based on siamese network were proposed. F values can reach 90.8% and 93.0%, respectively.