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Implementation of Web Log Mining Device Under Apriori Algorithm Improvement and Confidence Formula Optimization

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  • Lihua Zhu

    (Changzhou College of Information Technology, China)

Abstract

With the increasing number of internet users, a large number of network alarm information increases, resulting in the increasing pressure of SMS gateway and frequent alarm delay. Therefore, in order to effectively improve the above problems, the article is based on the improved Apriori algorithm and confidence formula, points and grabbing module, model training module and the test evaluation module device, three steps to realize the web log mining and mining system design for the data acquisition module, data preprocessing module, mining model building blocks, mining model checking module and mining model analysis and evaluation module five modules. Finally, the Python program was used to verify the test data of about two million pieces of original alarm data in a company's network management database for a consecutive month. The verification results show that the design of this paper has greatly reduced the number of original alarms and completed the merging of related rules.

Suggested Citation

  • Lihua Zhu, 2020. "Implementation of Web Log Mining Device Under Apriori Algorithm Improvement and Confidence Formula Optimization," International Journal of Information Technology and Web Engineering (IJITWE), IGI Global, vol. 15(4), pages 53-71, October.
  • Handle: RePEc:igg:jitwe0:v:15:y:2020:i:4:p:53-71
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