Recommendation algorithms aim at proposing “next” pages to a user based on her current visit and the past users’ navigational patterns. In the vast majority of related algor...
We study personalized web ranking algorithms based on the existence of document clusterings. Motivated by the topic sensitive page ranking of Haveliwala [19], we develop and imple...
In this paper, we attempt to improve the effectiveness and the efficiency of query-dependent link-based ranking algorithms such as HITS, MAX and SALSA. All these ranking algorith...
This paper explores the use of social annotations to improve web search. Nowadays, many services, e.g. del.icio.us, have been developed for web users to organize and share their f...
Abstract. In the rapidly evolving and growing environment of the internet, web site owners aim to maximize interest for their web site. In this article we propose a model, which co...