基于知识图谱的用户生成内容平台中碎片化知识整合研究

Research on Fragmentation Knowledge Integration in User-generated Content Platform Based on Knowledge Graph

针对用户生成内容(UGC)平台中存在的知识碎片化、缺乏系统性等问题,提出一种基于知识图谱构建完整知识体系的方法。首先通过对碎片化知识的挖掘与筛选得到相关知识点集,然后将个体知识整合成群体知识,进而形成用户个体知识集—碎片化知识点集—个体知识图谱—群体知识图谱的持续循环反馈模型,最后抓取知乎平台的特定知识主题作为研究数据。研究表明,由碎片化知识整合形成的群体知识,一方面有助于主题知识的表达与交流,另一方面有利于用户有效开展知识补全与系统学习。

Aiming at the problems of fragmentation and lack of systematization of knowledge in user-generated content(UGC) platform, this paper proposes a method to construct a complete knowledge system based on knowledge graph. Firstly, through the mining and screening of fragmented knowledge, the relevant knowledge points are obtained,and then the individual knowledge is integrated into group knowledge. Then, a continuous circular feedback model of user individual knowledge set-fragmentation knowledge point set-individual knowledge graph-group knowledge graph is formed. Finally, the specific knowledge topic of Zhihu platform is captured as research data. The research shows that the group knowledge formed by the integration of fragmented knowledge is beneficial to the expression and exchange of subject knowledge on the one hand, and to the effective knowledge completion and systematic learning of users on the other hand.