Time Sensitivity for Personalized Search

The user profile has been considered, in the literature, as the most important contextual element which can improve the accuracy of the search. It is integrated into the process of information retrieval in order to improve the user experience while searching for specific information. In addition, as time factor has gained increasing importance in recent years, the temporal dynamics are introduced to study the user profile evolution that consists mainly of capturing the changes of the user behavior, interests and preferences, and updating the profile accordingly. We propose, in this paper, a generic time-sensitive user profile that is implicitly constructed as a vector of weighted terms in order to find a trade-off by unifying both current and recurrent interests. The popularity of Social Media makes it as an invaluable source of data used by users to express, share and mark as favorite the content that interests them... For this reason, we modeled the user profile according to a set of data collected from Twitter, i.e a social networking and microblogging service. Then, we apply our re-ranking process to a Web search system in order to adapt the user's online interests to the original retrieved results. The results of the experiments proved the significance of adding a temporal feature by comparing our method with baselines models that do not consider the user profile dynamics.