中文摘要：

[目的/意义]为了从海量数据中发现不易被发现的有价值的异类知识,避免知识的流失,从系统视角来对异类知识和离群点进行了探索。[方法/过程]首先对异类知识和离群点检测研究进行梳理。其次采用SNA,数据源采用中国知网和EBSCO为基础收录相关文献信息,利用文献题录信息分析软件BIBEXCEL构建共词矩阵,使用UCINET绘制了共现图,对离群点的高频关键词共现性和高产作者合著情况进行分析。并提供了可视化的图形来揭示研究该领域的发展趋势和现状。[结果/结论]研究结果表明现阶段对于异类知识的研究主要聚焦于outlier的挖掘和算法的提出、改进方面,而对异类知识管理机理方面的相关研究很少,不仅缺乏足够重视而且没有进行深入研究的探索。

英文摘要：

[ Purpose/Significance ] In an effort to avoid knowledge losing and find valuable outlier knowledge that is hard to discover from massive data, this paper discusses the outlier knowledge and outliers from a systematic perspective. [ Method/Process ] Firstly, this paper summarizes the literature of outlier knowledge and outlier detection. Then, taking the papers from CNKI and EBSCO as data source, using Bibliographic information analysis software（BIBEXCEL） to build the co-word matrixes and UCINET to draw co-occurrence map to analyze the high frequency keywords co-occurrence network and the high frequency collaboration network in this field, the paper provides a visual graph to reveal the development trends and the status quo. [ Result/Conclusion ~ The results show that the current study on outliers knowledge mainly focuses on outlier mining and the proposal and improvement of algorithms, while the mechanism of outlier knowledge management still lacks adequate attention, the related research is limited and the exploration lacks depth.