Computer Science

Computer Science ›› 2021, Vol. 48 ›› Issue (2): 93-99.doi: 10.11896/jsjkx.200900039

• Database & Big Data & Data Science • Previous Articles     Next Articles

Outlier Detection and Semantic Disambiguation of JSON Document for NoSQL Database

LIU Li-cheng, XU Yi-fan, XIE Gui-cai, DUAN Lei   

  1. School of Computer Science,Sichuan University,Chengdu 610065,China
  • Received:2020-08-04 Revised:2020-09-25 Online:2021-02-15 Published:2021-02-04
  • About author:LIU Li-cheng,born in 1995,master candidate,is a student member of China Computer Federation.His main research interests include data mining and knowledge engineering.
    DUAN Lei,born in 1981,Ph.D,professor,Ph.D supervisor,is a senior member of China Computer Federation.His main research interests include data mining,health-informatics and evolutionary computation.
  • Supported by:
    This work was supported by the National Natural Science Foundation of China(61972268).

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Abstract: With the development of information technology,traditional relational database cannot be used for storage due to multi-source heterogeneity,strong scalability and explosive growth of data in materials and other related fields.Therefore,NoSQL can be used with the charactersitics of schemaless storage and high scalability to solve this problem.As a common data storage format for NoSQL databases,JSON is popular for its simplicity and flexibility.However,NoSQL databases lack schema information,and JSON documents need to be validated and analyzed before being stored in the database.At present,most methods verify the normalization of JSON document format based on JSON schema,which cannot effectively solve the problem of exception detection and semantic ambiguity of JSON document.Therefore,a JSON document outlier detection and semantic disambiguating model for NoSQL database is proposed,named doctorJSON.Based on JSON schema,the model designs outlier detection algorithm deout JSON and semantic disambiguation algorithm disemaJSON to detect the outlier and disambiguation in JSON documents.The vali-dity and efficiency of the model are verified by experiments on the real and synthetic datasets.

Key words: JSON document, JSON schema, NoSQL database, Outlier detection, Semantic disambiguation

CLC Number: 

  • TP311
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