摘要
提出了一种引入信息熵的改进型模糊C均值聚类算法,用来对企业客户进行模糊聚类,以分析获取客户的知识需求,为客户提供个性化的知识推送服务。通过实验分析,证明了该方法的有效性,从而提高了企业知识推送的及时性和准确性。
In this paper,the fuzzy C-means clustering algorithm is improved for enterprise customers fuzzy clustering by introducing the concept of information entropy.Based on this,it＇s easy to analyze the customers＇ knowledge demand and provide targeted knowledge push services.The experiment proves that the method is effective and has improved the timeliness and accuracy of the enterprise knowledge push services.
出处
《计算机系统应用》
2010年第1期104-107,共4页
Computer Systems & Applications
关键词
知识需求
知识推送
信息熵
模糊聚类
FCM
knowledge demand
knowledge push
information entropy
fuzzy clustering
