CRANAI: a new search model reinforced by combining a ranking algorithm with author inputs

Abstract

The explosion of information on the Internet has made search engine become the main method for users to find information on the Web. In this paper, we propose a new search model by combining a hyperlink-based page ranking algorithm with author inputs. The page ranking algorithm measures page importance by calculating the page weight based on incoming and outgoing hyperlinks in the page. The author input takes into account the weight of relevance in terms of keywords or phrases of a page specified by the page creators. Our evaluation shows that the proposed search method performs better than that using only the page ranking algorithm