P-Download: A New Personalization Approach for a Content-Based Search System

Abstract

With the explosive growth of information provided on the Web, personalization of search continues to be an important issue, particularly in the context of content-based search systems as the Internet started to evolve from being a simple information provider to a rich content provider. Building upon the recent findings in personalization strategies, the present research proposes a new search personalization algorithm that creates a synergetic effect by combining the download information with the current state of the art click-based algorithm. By assessing the log data of a user’s personal clickhistory in relation to the download information, the proposed method offers substantial advantage in creating a more specific user profile for personalization. A large dataset from a real-life content-based search system has been analyzed and tested for the evaluation of the proposed personalization method. The results largely support the significance of the proposed approach, highlighting the importance of downloading information in content-based search systems as a key ingredient for effective personalization. The findings have practical implications for content search service providers.