统计学科技情报“知识图谱”教学工具的构建

Construction of Statistical Teaching Tools for Sci-tech Information“Knowledge Graph”

“新商科”概念下,针对教学需求扩大学科与产业融合信息覆盖面积,帮助学生降低知识体系成本,是统计学课程建设面临的核心挑战之一。为了使学生在知识整理过程中体验主动选择带来的个性化理解,帮助学生发掘统计学理论在新经济环境应用层面上的机遇,本文提出了一种基于科技情报“知识图谱”的教学辅助系统构建方案。该系统“建模+应用”模块中采用了基于机器学习聚类算法的LIFCW模型解决了实体节点重要性过度放大的问题。基于科技情报的节点价值判断,更利于突出新兴行业高价值节点的位置,方便后续后台服务器有针对性地形成优化信息追踪方案,帮助专业人才更有效地跟踪与分析新兴行业领域主要特征数据,判断和掌握统计学理论的应用价值。

It is a great challenge to expand the information coverage area of the integration of disciplines and industries and help students reduce the cost of knowledge systems in the curriculum building of“statistics”under the concept of“New Business”.In order to enable students to experience the personalized understanding brought by active choice in the process of knowledge collation and help them tap the opportunity of applying statistical theory in the new economic environment,this paper puts forward a processing scheme of teaching aids system based on the“Knowledge Graph”under the public sci-tech information.In the“Modeling&Application”module,LIFCW model based on a machine learning clustering algorithm is adopted to eliminate the problem of over-amplification of the importance of entity nodes.Moreover,the judgment on the importance of the entity node based on the sci-tech information is more conducive to highlighting the position of high-value nodes in emerging industries and facilitating the targeted formation of optimized information tracking schemes by subsequent background servers,as well as helping professionals to track and analyze the primary characteristic data of emerging industries more effectively,and judging and mastering the application value of statistical theory.