吉林大学学报(信息科学版) ›› 2021, Vol. 39 ›› Issue (5): 576-582.

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基于贝叶斯网络的集中化IT运维信息检索算法

张 明   

  1. 首都医科大学 附属北京朝阳医院, 北京 100020
  • 收稿日期:2021-03-31 出版日期:2021-10-01 发布日期:2021-10-01
  • 作者简介:张明(1987— ), 男, 北京人, 首都医科大学工程师, 主要从事 IT 基础工程建设年份研究, (Tel)86-13811463611(E-mail)uuuu5541@126.com。
  • 基金资助:
    国家自然科学基金资助项目(60403019)

Centralized IT Operation and Maintenance Information Retrieval Algorithm Based on Bayesian Network

ZHANG Ming   

  1. Beijing Chao-Yang Hospital, Capital Medical University, Beijing 100020, China
  • Received:2021-03-31 Online:2021-10-01 Published:2021-10-01

摘要: 为适应集中化 IT 系统运维管理形式, 提高用户检索正确率, 增强用户服务质量, 提出了基于贝叶斯网络 的集中化 IT 运维信息检索算法。 从运维战略、模式、流程等方面分析 IT 运维体系架构, 明确用户提交检索申 请到结果反馈的整体流程; 对文本信息做预处理, 实现用户浏览内容结构化显示, 计算用户特征矢量; 利用有 向图表示贝叶斯网络拓扑结构, 通过获取术语节点与文件节点的先验概率, 推理文件与检索之间的概率关系, 过滤冗余信息; 建立样本空间, 将信息检索问题变换为在样本空间中的概念匹配问题, 获取文件和检索的关联 函数表达式, 并对其做简化处理, 完成运维信息检索模型构建。 仿真实验表明, 该方法可提高信息检索的查全 率与查准率, 减少网络负载。

关键词: 贝叶斯网络, 集中化 IT, 运维信息检索, 样本空间, 关联函数

Abstract: In order to adapt to the centralized IT system operation and maintenance management form, to improve the user retrieval accuracy and enhance the user service quality, a centralized IT operation and maintenance information retrieval algorithm based on Bayesian network is proposed. We analyze the IT operation and maintenance architecture from the aspects of operation and maintenance strategy, mode and process, defines the overall process from the user submitting the retrieval application to the result feedback; preprocesses the text information to realize the structured display of user browsing content and calculate the user feature vector; uses the directed graph to represent the Bayesian network topology, and obtains the prior probability of the term node and the file node for reasoning In order to complete the construction of operation and maintenance information retrieval model, the probability relationship between file and retrieval is used to filter redundant information. The sample space is established to transform the information retrieval problem into the concept matching problem in the sample space, and the correlation function expression of file and retrieval is obtained and simplified. Simulation results show that the method can improve the recall and precision of information retrieval, and reduce the network load.

Key words: bayesian network, centralized it, operation and maintenance information retrieval, sample space; correlation function

中图分类号: 

  • TP318. 2