这种检索方法在文本聚类的基础上,基于概念空间并与传统的关键词检索相结合能够帮助用户快速、准确地定位所需要查找的信息。
Based on concept space and text clustering technique as well as traditional keyword searching method, it could help users to locate the information they need quickly and precisely.
然而,中文网络短文本固有的关键词词频低、存在大量变形词等特点,使得难以直接使用现有面向长文本的聚类算法。
Since Chinese network short text is less of keywords and full of anomalous writings, the traditional text clustering method is not directly suitable for network short text clustering.
针对基于章节目录的分类方式过于依赖特定教材的不足,提出了基于关键词聚类的问题模糊分类方法。
Aimed at the lack of the old classification algorithm, the paper presents a question fuzzy classification algorithm based on clustering of .
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