With the deepening of economic globalization and the integration of the world economy, domestic and foreign companies are constantly developing. The trend of company expansion, diversification of business scope, transnationalization of business areas, and grouping of organizational forms has become increasingly obvious. Under the situation that enterprise group companies have become an important part of the market economy, group company financial management has also become an issue of great concern to the management and investors of various group companics, and the corporate financial management mode is the core of group company financial management. This paper studies the design of the financial management optimization system based on the multi-label classification algorithm of embedded feature extraction.


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    Titel :

    Application of Multi-Label Classification Algorithm Based on Embedded Feature Extraction in Financial Management Optimization System


    Beteiligte:
    Chunlei, Dai (Autor:in) / Jing, Bai (Autor:in)


    Erscheinungsdatum :

    02.12.2021


    Format / Umfang :

    894670 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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