摘要
[目的/意义]构建知识类微博信息质量的评价指标体系与评价模型,为知识类微博信息质量的提升和微博知识服务的改善提供参考。[方法/过程]通过文献调研与问卷调研,确立评价指标体系。收集用户评分数据进行实证分析,利用TOPSIS对30个知识类微博计算综合得分,并将数据输入RBF神经网络进行仿真训练。[结果/结论]测试结果显示,所建立的知识类微博信息质量评价模型的仿真值与实际评分值的误差均在6%以内。该模型能够较准确地拟合用户评分数据,适用于复杂多维指标体系下的微博信息质量评价场景,对知识类微博及其他类型的微博信息质量评价具有一定的借鉴意义。
[Purpose/Significance]The evaluation indicators system and evaluation model of knowledge-based microblog information quality are constructed to provide reference for the improvement of knowledge-based microblog information quality and microblog knowledge services.[Method/Process]The evaluation index system was established through literature research and questionnaire research.User rating data were collected for empirical analysis,and TOPSIS was used to calculate the comprehensive score of 30 knowledge-based microblogs,and the data was input into RBF neural network for simulation training.[Result/Conclusion]The test results show that the error between the simulation value and the actual score value of the knowledge-based microblog information quality evaluation model established in this paper is within 6%.The model can accurately fit the user scoring data,and is suitable for the microblog information quality evaluation scenario under the complex multi-dimensional index system,and has certain reference significance for the knowledge-based microblog and other types of microblog information quality evaluation.
作者
尤瑾
朱学芳
You Jin;Zhu Xuefang(School of Information Management,Nanjing University,Nanjing 210023;Jiangsu Key Laboratory of Data Engineering and Knowledge Service,Nanjing University,Nanjing 210023)
出处
《图书情报工作》
CSSCI
北大核心
2023年第13期122-132,共11页
Library and Information Service
关键词
知识类微博
信息质量评价
评价指标
用户视角
TOPSIS
RBF
knowledge-based microblog
information quality evaluation
evalution index
users'perspec-tive
TOPSIS
RBF
作者简介
尤瑾,硕士研究生;通信作者:朱学芳,教授,博士,E-mail:xfzhu@nju.edu.cn。
