Experiments show that the clustering system based on this algorithm can depose millions of abnormal short texts per hour with high accuracy.
实验表明，基于该算法的聚类系统对于大量的变异短文本处理速度可以达到每小时百万级以上，并且有比较高的准确率。
Realize the clustering algorithm part of the recommendation system based on collaborative filtering and evaluate it.
对基于聚类的协同过滤推荐系统的聚类算法进行了实现和评价。
Using HowNet's complete knowledge system to construct Concept Dictionary and Concept Hierarchy, we realized a kind of Chinese text clustering algorithm based on concept.
利用知网较完备的知识体系来构造概念词典和概念层次结构，实现了一种以知网为背景知识的基于概念的中文文本聚类算法。
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