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Automatic Document Data Storage System Based on Machine Learning

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Web and Big Data (APWeb-WAIM 2020)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12318))

Abstract

Document storage management plays a significant role in the field of database. With the advent of big data, making storage management manually becomes more and more difficult and inefficient. There are many researchers to develop algorithms for automatic storage management(ASM). However, at present, no automatic systems or algorithms related to document data has been developed. In order to realize the ASM of document data, we firstly propose an automatic document data storage system (ADSML) based on machine learning, a user-friendly management system with high efficiency for achieving storage selection and index recommendation automatically. In this paper, we present the architecture and key techniques of ADSML, and describe three demo scenarios of our system.

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Acknowledgement

This paper was partially supported by NSFC grant U1866602, 61602129, 61772157.

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Correspondence to Hongzhi Wang .

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Yan, Y., Wang, H., Zou, J., Wang, Y. (2020). Automatic Document Data Storage System Based on Machine Learning. In: Wang, X., Zhang, R., Lee, YK., Sun, L., Moon, YS. (eds) Web and Big Data. APWeb-WAIM 2020. Lecture Notes in Computer Science(), vol 12318. Springer, Cham. https://doi.org/10.1007/978-3-030-60290-1_45

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  • DOI: https://doi.org/10.1007/978-3-030-60290-1_45

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-60289-5

  • Online ISBN: 978-3-030-60290-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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