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"Big data" Analysis for Inventory Diagnosis on A Publishing House

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DOI: 10.23977/infkm.2021.020101 | Downloads: 6 | Views: 1174


Li Zhou 1


1 Chongqing University Press, Chongqing, China

Corresponding Author

Li Zhou


According to the statistics of the State Administration of Press, Publication, Radio, Film and Television, the national Xinhua Bookstore system and publishers self-run publishing units are facing an increasing inventory year by year. At the end of the year 2014, inventories have exceeded the 100 billion yuan mark. Big data analysis is beginning to attract the attention of all walks of life. Publishing house inventory data is also a kind of big data, which can be used as small data in big data for definition and characteristic analysis. This work analyzed the ultimate data of A Publishing House-inventory "big data", and subdivided its inventory composition data into four aspects including textbooks, books, topic selection sections and inventory turnover rate. With the help of reverse inference, problems in various links of the publishing house were diagnosed, such as market research, topic selection planning, production, marketing, etc. The decision of optimizing the publishing house was then adjusted accordingly, making it possible for the publishing house with its inventory to develop in a healthy way.


Publishing House Inventory; Data; Turnover Rate; Reverse Analysis and Diagnosis; Sound Development


Li Zhou. "Big data" Analysis for Inventory Diagnosis on A Publishing House. Information and Knowledge Management (2021) Vol. 2: 1-9. DOI:


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