利用TF-IDF算法优化地方性新闻搜索

Local News Search of TF-IDF

对如何优化地方性新闻搜索进行了探讨,通过运用IKAnalyzer所提供的开源程序对每个网站的源代码中的中文进行分词处理,再利用TF-IDF算法对每个网站的关键词进行权重的计算,由高到低列出关键词向量。将这些网站的关键词向量逐一与标准关键词向量进行比较,从而将网站进行分类处理。以达到快速准确的搜索目的。

This thesis aims to discuss how to optimize the Local News Search.By using the open source program provided by IKAnalyzer we can firstly break the source code of the website,and then calculate the weight of each word with TF-IDF arithmetic.In this way,key words vector can be given out and then we can compare each word with the standard one.With these methods,we can part the websites and find out our aim fast and accurately.