The research of professional meta-search engine result based on genetic algorithm

Abstract

The query results returned from the meta-search engine come from the independent search engine and the results will be evaluated the professional correlation; additional information must be dogged beyond its location information. This paper proposes a web page ranking algorithm based on genetic algorithms, and discusses the principle of the algorithm and implementation process, researches and realizes the meta-search engine in the field of training. Based on the fully dig of web text information and combined with the web professional correlation algorithm given by genetic algorithm, this paper extracts the features of professional website. Experimental results show that the engine has a high professional information filtering and sorting capabilities.