Simultaneous personalized topic of interest and hub promotin of PageRank

The current algorithms for ranking pages of the WWW are based on authority or hub values of pages, which are techniques built to serve all users, independent of the special needs of any individual user. Personalization of Web ranking is to carry out ranking for each user incorporating his/her interests. This paper considers the user's topic of interest, proposing a novel technique, which is based on the ODP category We present P PankRank, and SHP&P PageRank, new algorithms for ranking pages exploring the link structure of the Web graph. P PankRank modifies the PageRank personalization vector E through non-uniform normalized topic of interest weight. Besides this technique, SHP&P PageRank also introduces its criterion for out-links of pages, which gives a more complete view of page importance by biasing the authority measure towards hub values of pages. Finally, we present an evaluation of these algorithms experimentally.