基于知识融合的政务信息化项目多专家审批意见整合  

Integrating Expert Reviews for Government Information Projects with Knowledge Fusion

作　　者：华斌[1] 吴诺[1] 贺欣 Hua Bin;Wu Nuo;He Xin(School of Science and Technology,Tianjin University of Finance and Economics,Tianjin 300222,China)

机构地区：[1]天津财经大学理工学院,天津300222

出　　处：《数据分析与知识发现》2021年第10期124-136,共13页Data Analysis and Knowledge Discovery

基　　金：天津市信息化专项资金项目(项目编号:津党网信函(2018)146号)的研究成果之一。

摘　　要：【目的】提出一种利用知识融合实现政务信息化项目多专家审批意见短文本的整合方法,实现以认知层知识融合为主导的综合意见生成。【方法】通过对专家意见进行内容挖掘完成知识获取;利用目标知识概念树与自定义方法对其进行实体层次性语义挖掘;利用领域本体在文本结构模型基础上实现微观和宏观层的知识融合并生成综合意见。【结果】对比原始多专家审批意见,基于知识融合生成的综合意见信息量增加0.19,所含知识元的平均比值达到115.38%,均显示了所提方法的有效性。【局限】受到专家意见语言规范程度与领域知识完整度的影响。【结论】利用科学的知识补充与表示,所提方法较传统的短文本整合方法显示出更好的问题针对性、知识覆盖程度和可推广性,也取得了良好的应用效果。[Objective]This paper proposes a new method to integrate the short texts of multi-expert reviews for the same government information project,aiming to generate comprehensive opinion with knowledge fusion at the cognitive level.[Methods]First,we extracted knowledge from the reviews through content mining.Then,we analyzed semantics of these reviews with target knowledge concept tree and customized method.Third,we finished knowledge fusion at the micro and macro levels based on the text structure model and domain ontology.[Results]Compared with the original texts,the amount of information provided by our method was increased by0.19,while the average ratio of knowledge elements reached 115.38%.[Limitations]The proposed method could be affected by the language of expert reviews and the integrity of domain knowledge.[Conclusions]Our new method could effectively integrate short texts from various fields.

关 键 词：政务信息系统 项目管理 意见挖掘 知识融合 文本整合 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]