An Implemented Rank Merging Algorithm for Meta Search Engine

In order to improve the precision of meta search engine, In the foundation of analysis two kinds traditional merging algorithm of meta search engine, and the disadvantage of two algorithms are given, one kind of new about the results merging method based on the combination of position and snippets/titles is proposed. which integrates these two factors, the related degree between the position information of query results and the query words, the similarity between query results’ snippets and the query words. Then take a popular measure for evaluating the effectiveness of search engines to analysis the results, The results of the experiment show that, the average precision of this method is higher than popular component search engines now, and it also proved that result merging in a meta search engine, considering the information of the position and title/snippet of the search results at one time, the accuracy of the meta search engine will be better.