基于知识图谱与大数据的基建领域对话信息挖掘算法

Dialogue information mining algorithm in infrastructure field based on knowledge graph and big data

对基建项目对话信息的有效挖掘是基建领域发展的必然趋势,也是实现基建项目高质量发展的必要手段,基于知识图谱与大数据研究基建领域对话信息挖掘算法,以全生命周期理论对应基建项目建设全过程,按照需求分析设计基建项目对话信息数据库,针对数据库应用逻辑定义对话信息数据流图谱。通过数据流图谱的展现形式,选择知识图谱算法标记对话信息类型标签,以可扩展模式确定基建领域内对话信息的具体关系。为保证确定对话信息关系具有关联性,通过大数据技术中相似评估方式,在对应信息关系之间计算两者相似度,通过相似度合并计算数据关联概率,实现全局领域内的对话信息挖掘,完成算法设计。实验结果表明,按照基建工程中不同的对话信息类型进行挖掘验证,新算法可以实现不同信息元素的精准挖掘,具有一定应用价值。

The effective mining of dialogue information of infrastructure projects is an inevitable trend in the development of infrastructure field,and also a necessary means to achieve high-quality development of infrastructure projects.Based on knowledge graph and big data,the algorithm of dialogue information mining in infrastructure field is studied.Corresponding to the entire process of infrastructure project construction with the theory of full lifecycle,we design a dialogue information database for infrastructure projects based on demand analysis,and define a dialogue information data flow graph for database application logic.Through the presentation form of the data flow map,select the knowledge graph algorithm to mark the dialogue information type label,and determine the specific relationship of the dialog information in the infrastructure field in an extensible mode.In order to ensure the determined relationships of dialogue information are correlated,the similarity between the corresponding information relationships is calculated through the similarity evaluation method in big data technology.The data correlation probability is calculated by combining the similarity,to realize the dialog information mining in the global domain and complete the algorithm design.The experimental results show that the new algorithm can achieve precise mining of different information elements by mining and validating different types of dialogue information in infrastructure engineering,demonstrating practical value.