检索规则说明:AND代表“并且”;OR代表“或者”;NOT代表“不包含”;(注意必须大写,运算符两边需空一格)
检 索 范 例 :范例一: (K=图书馆学 OR K=情报学) AND A=范并思 范例二:J=计算机应用与软件 AND (U=C++ OR U=Basic) NOT M=Visual
作 者:徐鹏[1] 龚伟 宋俊典[3] Xu Peng;Gong Wei;Song Jundian(The Third Research Institute of the Ministry of Public Security,Shanghai 200031,China;Shanghai Metro First Operation Co.,Ltd.,Shanghai 200003,China;Shanghai Development Center of Computer Software Technology,Shanghai 200112,China)
机构地区:[1]公安部第三研究所,上海200031 [2]上海地铁第一运营有限公司,上海200003 [3]上海计算机软件技术开发中心,上海200112
出 处:《计算机应用与软件》2024年第5期171-176,273,共7页Computer Applications and Software
摘 要:命名实体识别是一种有效的设备运行日志分析方法,不仅提高了故障检测的准确度,而且为智能运维策略的优化提供了强有力的支持。鉴于设备运行日志的专业性和复杂性,提出一种基于机器阅读理解的设备故障命名实体识别方法,该方法通过将特定的实体类别转化为自然语言查询,并将实体类别信息融合到这些查询中,有效地克服了传统方法在标签语义信息上的不足,并在实体边界定位的准确性上取得了显著提升。实验表明该方法在设备故障命名实体识别的准确性和有效性方面明显优于现有的基线方法。Named entity recognition plays a crucial role in analyzing equipment operation logs,not only enhancing the accuracy of fault detection but also providing strong support for the optimization of maintenance strategies.Given the professionalism and diversity of equipment operation logs,this paper proposes a fault entity recognition method based on machine reading comprehension.This method transformed specific entity categories into natural language queries and integrated entity category information into these queries,which effectively overcame the deficiencies of traditional methods in label semantic information and significantly improved the accuracy of entity boundary positioning.Experiments conducted on a dataset for equipment fault entity recognition show that this method excels in accurately identifying equipment fault entities,significantly outperforming existing baseline methods.
分 类 号:TP391.1[自动化与计算机技术—计算机应用技术]
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在链接到云南高校图书馆文献保障联盟下载...
云南高校图书馆联盟文献共享服务平台 版权所有©
您的IP:216.73.216.7