As digital collections expand, the importance of the temporal aspect of information has become increasingly apparent. The aim of this paper is to investigate the effect of using long-term temporal profiles of terms in information retrieval by enhancing the term selection process of pseudo-relevance feedback (PRF). For this purpose, two temporal PRF approaches were introduced considering only temporal aspect and temporal along with textual aspect. Experiments used the AP88-89 and WSJ87-92 test collections with TREC Ad-Hoc Topics 51-100. Term temporal profiles are extracted from the Google Books n-grams dataset. The results show that the long-term temporal aspects of terms are capable of enhancing retrieval effectiveness.