FlexiRank: An Algorithm Offering Flexibility and Accuracy for Ranking the Web Pages

Abstract

The existing search engines sometimes give unsatisfactory search result for lack of any categorization. If there is some means to know the preference of user about the search result and rank pages accordingly, the result will be more useful and accurate to the user. In the present paper a web page ranking algorithm is proposed based onsyntactic classification of web pages. The proposed approach mainly consists of three steps: select some properties of web pages based on user’s demand, measure them, and give different weightage to each property during ranking for different types of pages. The existence of syntactic classification is supported by running fuzzy c-means algorithm and neural network classifier on a set of web pages. It has been demonstrated that, for different types of pages, the same query string has produced different page ranking.