The Research Of Professional Meta-search Engine Technology Based On Genetic Algorithm

Nowadays with the rapid and vigorous development of Internet technology, Internet penetration rate has been rising in a straight line, and the number of Internet users also has been on the increase exponentially. Due to the increasing number of Internet users, the total amount of Internet information also increases in a large amount every day. At present, the total amount of Internet information is very large, and now the Internet users’consciousness of using the Internet to find information has improved constantly. However, different users" demands for professional information vary from each other and Internet information has been an explosive growth. These make it very difficult for users to find the real information they need only by relying on independent search engine. Therefore, it becomes the primary task of major search engine operators to settle the issue of search results of users to relevant fields aiming at different fields and make the results more user-friendly and demand-targeted.This paper analyses in depth the relevant theories of each individual search engine and related theories of meta-search engine information, and by combining their own advantages and improving each other’s shortcomings, the author has established a professional meta-search engine oriented to training areas. Since the search engine in this paper is designed for professional fields, it is necessary to analyze the professional association of the results of every web page. To compute the webpage relevance, a web correlation model must be established which can predict the value of calculating the webpage relevance, sort the page according to the value, and then return the results to the query user. This thesis filters out the keywords that highly influence the professional page sorting based on the improved genetic algorithm, and then creating a page correlation model, at last, testing the model to verify its reliability.This paper mainly talks about the following aspects:building a webpage relevance model as the web ranking optimization algorithm according to the improved genetic algorithm; establishing a professional meta-search engine oriented to education training field; introducing the design and implementation of related modules, and finally evaluating and analyzing the searching results of this search engine.