一种基于聚类技术的全文检索与推介系统的构建

Construction of One Kind of Full-text Searching & Recommending System Based on Clustering

近年来,搜索引擎的发展可谓突飞猛进,排序算法也日新月异,但相关搜索推介这项功能却进展缓慢,无法为用户提供令人满意的有价值的关键词。本项目是专门为了解决这个问题而进行研究的,采用单词到文档,文档到聚类,聚类再回归单词的语义检索流程,完成了K-means聚类算法以及TFIDF权重算法的Java实现。通过此系统,用户不仅可以找到包含指定关键词的网页,还会收到与该关键词关联最紧密的其他关键词推介,协助用户进一步发掘信息。

In recent years,the development of the search engine and the sorting algorithm is updating fast.But the recommending system,which cannot provide valuable keywords in the past,is barely evolved.Our project is specialized in order to solve this problem.This project goes from word to document,and from document to cluster,then from cluster to the word which is to be returned.It realized the K-means clustering algorithm and the TFIDF weight algorithm with Java.Users can find not only the web pages including the specific keyword,but also the most valuable keyword recommended which is to help them finding information related.