一种基于用户兴趣的STC改进算法

A New STC Algorithm Based on User Interest

作为一种常用的在线文档聚类算法,STC算法聚类结果在用户个性化方面存在不足。改进后的算法结合用户兴趣模型,通过增加基类选择因子和改善基类合并规则来进行改进,实现基于用户兴趣特征的个性聚类效果。实验表明,改进后的算法具有较好的准确性和效率。

STC algorithm is an online document clustering algorithm commonly used. There are some deficiencies in users＇ personalization of the clustering results. The improved algorithm combined with the users＇ interest model can implement the characteristic clustering results by increasing the base class selection factor and improving the merge rules of the base class. The experiments show that the improved algorithm has better accuracy and efficiency.