Emphasizing temporal-based user profile modeling in the context of session search.

In this paper, we aim at modeling the user profile containing timely relevant information extracted from his interactions with search engines. We considered a time-sensitive user profile that provides relevant and fresh information inferred from his submitted queries, reformulated queries and clicked results. We used a unique profile that integrates current and recurrent interactions within a session giving more importance to recent interactions without ignoring the old ones. We conducted experiments using the 2013 TREC Session track and the ClueWeb12 collection that showed the effectiveness of our approach compared to state-of-the-art ones.