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。
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.
作者
张明
ZHANG Ming(Beijing Chao-Yang Hospital,Capital Medical University,Beijing 100020,China)
出处
《吉林大学学报（信息科学版）》
CAS
2021年第5期576-582,共7页
Journal of Jilin University（Information Science Edition）
基金
国家自然科学基金资助项目(60403019)。
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
bayesian network
centralized it
operation and maintenance information retrieval
sample space
correlation function
