摘要
随着Internet的迅速发展,人们面对信息爆炸的现实。因此,需要根据用户的查询意图进行推荐。基于此,提出一种计算查询词相似度的方法,利用K-means对查询词进行聚类并计算聚类簇中心,当用户输入查询词后计算该查询词与每个聚类簇中心的相似度并降序排列,选取相似度最大的两个聚类簇对其进行查询推荐。
With the rapid development of Internet, people are facing the reality of information explosion.Therefore, we need to recommend according to the user＇s query intention. Based on this, a computationmethods of query similarity was introduced, which used k-means to query clustering and calculate the clus-tering center, then calculated the similarity between query and each cluster center when the user input que-ry and ranked in descending order, then selected the queries of the maximum similarity of two clusters torecommendation.
出处
《河南科技》
2016年第7期50-51,共2页
Henan Science and Technology
