CAJ | 학술논문

传统的演化聚类算法大多是基于单个时间截面进行问题求解，对于多时间截面的融合问题尚无有效的处理办法，造成了大量的知识浪费。从时间平滑框架出发，借鉴组合聚类思想，提出一种基于加权联合矩阵的演化聚类算法（WCEC）。实验表明，该方法不仅简单有效，而且对于数据点变化的演化情况具有较高的扩展性。
전통적연화취류산법대다시기우단개시간절면진행문제구해，대우다시간절면적융합문제상무유효적처리판법，조성료대량적지식낭비。종시간평활광가출발，차감조합취류사상，제출일충기우가권연합구진적연화취류산법（WCEC）。실험표명，해방법불부간단유효，이차대우수거점변화적연화정황구유교고적확전성。
Compared with static clustering,evolutionary clustering can not only resist to the noise in short-term,but also re-flect the changing trend in long term.It has been widely used in dynamic community identification,financial product analysis and many other fields.Traditional evolutionary clustering focus on a single time step,while falls short of dealing with multiple ones.Based on the time smoothing framework,this paper put forward a weighted co-association matrix oriented evolutionary clustering(WCEC),which proved to be simple as well as scalable through experiments.