基于开放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  

Identifying Potential Disciplinary Collaboration Research Topics by Open Literature-based Discovery:Taking Information Science and Computer Science as Examples

作　　者：李长玲[1] 刘小慧[1] 刘运梅[1] 冯志刚[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》2018年第2期100-104,137,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"的成果之一;项目编号:16BTQ078

摘　　要：[目的/意义]用开放式非相关知识发现方法,以情报学与计算机科学为例,识别两学科中的潜在跨学科合作研究主题。[方法/过程]首先,以跨学科关键词共现网络为基础,构建网络中关键词的二维向量空间模型;其次,按照一定原则筛选中间词,建立关键词核心向量模型;然后,定义关键词向量模型的代入法运算,识别关键词的潜在跨学科合作研究主题;最后,计算每对潜在跨学科合作研究主题的合作潜力,并对识别结果举例分析其应用前景。[结果/结论]运用本文提出的开放式非相关知识发现方法,在实证研究中发现了情报学与计算机科学的潜在跨学科合作研究主题,希望该方法可以为学者的跨学科合作提供借鉴。[ Purpose/significance ] Taking Information Science and Computer Science as examples, this paper identifies their potential interdisciplinary collaboration research topics by open literature-based discovery. [ Method/process ] Firstly, based on the interdisciplinary keywords co-occurrence network, the paper builds the 2D space vector model of keywords. Then, the middle words are selected by certain rules, and the core vector model of the keywords is established. Next, the paper defines the substitution method of the keywords vector model to identify potential interdisciplinary collaboration research topics. Finally, the paper calculates the potential collaboration value between two topics that the paper has identified, and analyzes their future application. [ Result/ eonelusion~ by using the method of open literature-based discovery that the paper has proposed, the potential interdisciplinary col- laboration research topics between Information Science and Computer Science have been identified. This method can provide refer- ences for scholars to carry out interdisciplinary collaboration.

关 键 词：非相关知识发现 共现网络 跨学科合作 主题识别 

分 类 号：G353.1[文化科学—情报学]