Patent ID: 7502786
Filing Date: 2009-03-10
Classification: G06F,Y10S

Abstract:
1. A visual method for enhancing search result navigation, comprising: obtaining a first search result from a search engine; clustering the first search result to get clustering information; calculating the correlations between the clustering information and a ranked list of the first search result, and performing visualization processing on the clustering information; and displaying the visual cluster hierarchy and the ranked list of the first search result in a joint manner based on the correlations, wherein the first search result contains a predetermined number of search result entries in the search results produced by the search engine based on a query; wherein the displaying visual cluster hierarchy and the ranked list of the first search result in a joint manner comprises one of the following: wherein the step of clustering the first search result applies the Suffix Tree Clustering algorithm; wherein said method further comprises repeatable steps comprising: wherein the visual cluster hierarchy and the visual sub-clustering information form a tree structure, wherein the clusters contained in the visual cluster hierarchy are taken as root nodes and the visual sub-clustering information items contained in the visual sub-clustering information are taken as branch nodes, wherein the step of generating new query keywords comprises: combining the current query keywords with the name of the selected cluster to generate new query keywords, wherein the step of generating new query keywords comprises: wherein the relevant documents are the documents that have been read by the web user or the documents that belong to the selected cluster, and wherein the step of determining keywords in the relevant documents comprises: where value represents the weight of a word; tf represents the frequency at which the word appears in the relevant documents; where all documents represents the number of all the relevant documents, keyword documents represents the number of the relevant documents that contain this word; and