Preface RecTemp Nowadays a lot of data that can be used by Recommender Systems is continuously becoming available. With the evolution of Internet of Things, timestamped data is collected by many different sensors enabling the identification of temporal aspects of the various events. This wealth of data opens new research directions for discovering different temporal patterns in different domains (seasonal, monthly, weekly) and their impact. The workshop is focused on what can be discovered in such data from the temporal perspective and what are the current research challenges. 13 papers were submitted to the workshop and 11 of them were accepted. So, the full day workshop program was very rich and intensive. Different topics are covered in these papers: short term vs long term preferences, concept drifts in users tastes, in communities and applying deep learning techniques that consider sequences (Recurrent Neural Networks) for providing recommendations. Researchers were conducted in different domains (music, e-commerce, social tagging and news) on different publicly available datasets that contain timestamps, such as: RecSys Challenge 20151, 30Music2, MovieLens3, Netflix, Bibsonomy 4, NewsREEL 20175 and few more. While reasoning about the time, various time aspects were taken into consideration: by using timestamp to track user age; by incorporating dwell time from the timestamped dataset into RNN; by considering dynamics in community recommendations, like shift in users' community preferences and interests; by exploiting last common user interactions with their neighbors; by incorporating temporal item popularity into matrix factorization based model; by adding seasonality, trending (extracted from the timestamped data) into the RNN model for improving fashion recommendations; by using most recent interactions from the social tagging system and so on. We would like to thank the authors for their submissions and the RecSys workshop chairs for their guidance during the RecTemp workshop organization. We also would like to thank our great PC members that each one of them reviewed three submitted papers and provided an interesting and valuable insight to each one of them. The organization of RecTemp workshop was partially supported by the following projects: Human Information Behavior in the Digital Space (APVV-15-0508), Adaptation of access to information and knowledge artifacts based on interaction and collaboration within web environment (VG 1/0646/15), the Innovation Authority MAGNET InfoMedia project. 1 http://2015.recsyschallenge.com/challenge.html 2 http://crowdrec.eu/2015/11/30music-dataset-release/ 3 https://grouplens.org/datasets/movielens/ 4 https://www.kde.cs.uni-kassel.de/bibsonomy/dumps/ 5 http://www.clef-newsreel.org/dataset/ Workshop Organizers Maria Bielikova, Slovak University of Technology in Bratislava Veronika Bogina, University of Haifa Tsvi Kuflik, University of Haifa Roy Sasson, Google and Tel-Aviv University Program Committee Shlomo Berkovsky, CSIRO Robin Burke, DePaul University Peter Dolog, Aalborg University Dietmar Jannach, TU Dortmund Judy Kay, University of Sydney David Konopnicki, IBM Bamshad Mobasher, DePaul University Osnat Mokryn, University of Haifa Robert Moskovitch, Deutsche Telekom Laboratories at Ben-Gurion University Giuseppe Sansonetti, Roma Tre University Amit Tiroshi, Atlassian