Topic Hub Based Meta Search Engine

To improve the ranking result quality of meta search engine,the authors propose and design a ranking algorithm based on the component engines by topic hub values.The algorithm uses a set of topic relating words to learn the feature of the component engines and denotes them as topic hub values.The ranking algorithm calculates the global similarity of the results according to the topic hub values.The experiments show that the model can get a better ranking quality.