This paper firstly introduces text cluster and classification techniques that are the base techniques of topic detection and topic tracking. According to the features of blog, this paper designs the topic detection and topic tracking techniques.
本文首先介绍了话题检测和话题跟踪的基础技术文本聚类和分类技术,并针对Blog领域信息的特点设计了话题检测和话题跟踪技术。
参考来源 - 中文Blog热门话题检测与跟踪技术研究·2,447,543篇论文数据，部分数据来源于NoteExpress
Through analyzing about traditional clustering methods, we present the text clustering based on the community detecting algorithms, adopt it to cluster the text datas and have good effect.
通过对传统文本聚类的实现与分析，将复杂网络中的社区划分算法应用文本聚类中，实现基于社区划分算法的文本聚类，并取得一定的效果。
Given large data sets, whether they are text or numeric, it is often useful to group together, or cluster, similar items automatically.
对于大型数据集来说，无论它们是文本还是数值，一般都可以将类似的项目自动组织，或集群，到一起。
DM_GETCLUSTERS that returns a table of the clusters in the model together with a short text description about the field distribution in this cluster.
该函数返回一个表，其中包含模型中的集群，以及关于这个集群中字段分布的简短文本描述。
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