基于闭合式非相关知识发现的潜在跨学科合作研究主题识别——以情报学与计算机科学为例  

Research Topics Identification of Potential Interdisciplinary Collaboration Based on Closed and Irrelevant Knowledge Discovery

作　　者：刘小慧[1] 李长玲[1] 崔斌[1] 刘婷[1] 

机构地区：[1]山东理工大学科技信息研究所,山东淄博255049

出　　处：《情报理论与实践》2017年第9期71-76,共6页Information Studies:Theory & Application

基　　金：国家社会科学基金项目"基于量化与质性数据的跨学科合作行为研究"的成果;项目编号:16BTQ078

摘　　要：[目的/意义]在跨学科现象日趋明显的背景下,为促进学科融合发展,为跨学科合作研究提供新思路,文章运用闭合式非相关知识发现方法,对两学科的潜在跨学科合作研究主题进行识别,并发现潜在主题的关联过程。[方法/过程]基于跨学科关键词共现网络,综合运用Ucinet和VBA,筛选距离矩阵中距离为2的关键词对作为潜在跨学科合作研究主题;定义主题跨学科合作潜力指数(TICPI)及其计算公式,计算主题的跨学科合作潜力;定义联系路径的可行性强度(PV)寻找合作主题的最佳联系路径。[结果/结论]在以情报学与计算机科学为例的实证研究中,发现两个学科存在间接联系的非相关跨学科合作主题及其最佳联系路径。[ Purpose/significance] As interdisciplinary phenomenon has become increasingly obvious, in order to promote the development of discipline integration and provide new ideas for interdisciplinary collaboration, this paper uses closed and irrelevant knowledge discovery method to identify potential research topics of interdisciplinary collaboration and their association processes. [ Method/process ] Based on interdisciplinary keywords co-occurrence network, the paper first uses Ucinet and VBA to screen the keywords that the distance is 2 in distance matrix as potential interdisciplinary collaboration topics, Then defines Topic Interdisciplinary Cooperation Potential Index （TICPI） to calculate topic＇s cooperation potential, at last defines Practicable Value （PV） to find the best association path. [ Result/conclusion ] In the empirical research on Information Science and Computer Science, the paper finds their irrelevant cooperation topics that have indirect connection and the best association path of the topics.

关 键 词：潜在主题 跨学科研究 知识发现 主题识别 

分 类 号：G353.1[文化科学—情报学]