A narrow-domain entity recognition method based on domain relevance measurement and context information

Entity recognition is the basis of text mining. With the further development of knowledge-driven applications, types of target entities are increasingly subdivided. The lack of corpus and the limited number of entity have been the main challenges of entity recognition. Based on this observation, this paper proposes a weak-supervision method for recognizing entities from a specifically narrow domain by fusing domain relevance measurement and context information. The experimental result shows that the proposed method has high efficiency and accuracy without manual participation.