How to extract high-value knowledge quickly, accurately and comprehensively from high volume, and high variety data in vertical field, is a major issue to be solved in the intelligent construction of various fields. Knowledge extraction, which extracts large-scale structured knowledge from multi-source heterogeneous data, can provide a strong support for many applications, such as knowledge graph construction, automatic question answering, situation awareness and intelligent decision. In this paper, we first summarize the critic problems and challenges of knowledge extraction in vertical field by surveying the key technologies involved in knowledge extraction. Then, we propose a unified framework of knowledge extraction targeting for vertical field. This framework presents a detail solution for the key problems in knowledge extraction and indicates the potential research work to be carried out in the future.
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