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With the rapid development of related technologies in the field of natural language processing, as an upstream task of natural language processing, improving the accuracy of named entity recognition is of great significance for subsequent text processing tasks. However, due to the differences between Chinese and English languages, it is difficult to transfer the research results of English named entity recognition into Chinese research effectively. Therefore, the key issues in the current research of Chinese named entity recognition are analyzed from the following four aspects: Firstly, the development of named entity recognition is taken as the main clue, the advantages and disadvantages, common methods and research results of each stage are comprehensively discussed. Secondly, the Chinese text preprocessing methods are summarized from the perspective of sequence annotation, evaluation index, Chinese word segmentation methods and datasets. Then, aiming at the Chinese character and word feature fusion method, the current research is summarized from the perspective of character fusion and word fusion, and the optimization direction of the current Chinese named entity recognition model is discussed. Finally, the practical applications of Chinese named entity recognition in various fields are analyzed. This paper discusses the current research on Chinese named entity recognition, aiming to help researchers understand the research direction and significance of this task more comprehensively, so as to provide a certain reference for proposing new methods and new improvements.

To practice the development concept of "lucid waters and lush mountains are invaluable assets", and balance mineral development and ecological environment protection, it is urgent to carry out dynamic monitoring and scientific evaluation of the ecological environment in mining areas.Based on the characteristics of the ecological environment in mining areas, this paper analyzes the temporal and spatial change characteristics and differences of the ecological environment elements in the mining area, the impact mechanism of the mining and restoration activities on the ecological environment elements, and the cooperative evolution law of each element.Guided by the requirements on ecological environment monitoring and evaluation in mining areas in the new era, a technology framework for quantitative remote sensing-based monitoring and evaluation of the ecological environment in mining areas is proposed from the perspective of 'data-monitoring-evaluation-application'.The framework makes full use of multi-source big data in mining areas with remote sensing images as the main body and takes advantage of the emerging technologies such as artificial intelligence and quantitative remote sensing.This research archives quantitative monitoring and evaluation of the ecological environment elements in the mining areas with the features of high frequency, large-extent, long-term, continuous, all-factor observation and quantitative inversion, which can support the operational applications including mining activity monitoring, ecological environment diagnosis and early warning and restoration effect evaluation in mining areas.Finally, two real-world cases are introduced to illustrate the effectiveness and application flow of the proposed framework.