中文摘要：

作者同被引分析（ACA）方法是研究领域知识结构的重要手段,它能够发现跨领域知识关联的存在,借助一些辅助的分析方法和步骤也能够发现知识关联的内容.但作者同被引网络无法直接反映关联的内容,因此这种方法的实际应用效果受到一定限制.施引关键词与被引作者的交叉共现分析（CKCA）,能够清楚地发现科学领域中的学术流派及研究方向,以及流派中作者间关联的内容,发现在某一主题领域有重要贡献的研究人员.与作者同被引分析（ACA）相比,CKCA分析在揭示学术流派间、学术流派内节点间联系的能力更加出色,能够更准确的反应学术流派的研究主题和方向,并且具备了更高的可读性.

英文摘要：

ACA is the important research tool of the structure of knowledge, and has been widely used in many fields. We can found the association of the co-cited author by ACA, but can not know the mean of the association. By cross co- occurrence of citing keywords and cited author （CKCA） , there can be clearly found in the academic schools of science and research, and the detail mean of an association between author, and we can discovered a important researchers. Compared with the author citation analysis （ACA） , network diagram formed by CKCA was more readable, the group is very clear, specific, to more accurately reflect the type of research group theme and direction.