Abstract:Name ambiguity is a common phenomenon when one tries to search for someone's information in the Internet. In this paper, we have studied the web name disambiguation issue in detail. After extracting different features related to the name and then creating combined features by vector space model, we give priority to cluster the documents with high similarity by hierarchical clustering algorithm. Evaluated on the WePS data set, the proposed method showed its effectiveness in solving name disambiguation problem.