Adapting user's browsing behavior and web evolution features for effective search in medical portals

The World Wide Web, inform of medical and health related Web search services has been widely acknowledged as an important tool for accessing and distributing medical information. The efficiency of its use is hampered however to some extent, by the data overload and the poor organization and presentation of medical portals and sites in general. In this paper we propose an intelligent meta-search algorithm exclusively for health-related Web search, capable of self-adapting over the continuous changes that occur on medical sites, using a Web evolution adaptation mechanism. The algorithm also supports personalization features based on the user browsing behavior. The paper provides the implementation details of the proposed meta-search algorithm along with its initial assessment. The experimental results show the efficiency of the proposed algorithm in terms of relevancy on the re-ranked third-party results