Genetic Algorithm in Web Search using inverted index representation

This paper proposes genetic-based algorithm that uses inverted index model as a preprocessing step called GAWS. It is used as a method for finding best set of documents related to the entered user keywords. These keywords are divided into three types: main keywords, should exist keywords and should not exist keywords. Different sets of data are used to evaluate GAWS each of which is double of the initial space size. Experimental results show that GAWS demonstrate high quality and also found to be competitive with the standard search engines.