Preface The 23rd International Conference on User Modelling, Adaptation and Personalization (UMAP 2015) was held in Dublin, Ireland, between 29th of June and the 3rd of July, 2015. Similarly to poster and demonstration papers, late-‐breaking results contain original and unpublished accounts of innovative research ideas, preliminary results, industry showcases, and system prototypes, addressing both the theory and practice of User Modelling, Adaptation and Personalization. In addition, papers introducing recently started research projects or summarizing project results have also been welcomed. A total of 12 submissions were received. Similarly to the main tracks of the conference, each of them was reviewed by at least three members of the Program Committee. Submissions have been assessed based on their originality and novelty, potential contribution to the research field, potential impact in particular use cases, and the usefulness of presented experiences, as well as their overall readability. For these proceedings, 6 papers were accepted based on this process, for presentation at the UMAP 2016 conference, on the 1st of July 2015. They range in topics from: • • • • • basic adaptation technique exploration, such as paper "A Methodology for Discovering how to Adaptively Personalize to Users using Experimental Comparisons" by Joseph Jay Williams and Neil Heffernan, developing theoretical models for systematic explorations of versions of a particular artefact in experiments with people, to find out which best matches a particular type of person ; semantic web-‐inspired research, such as the paper "Using Basic Level Concepts in a Linked Data Graph to Detect User's Domain Familiarity" by Marwan Al-‐Tawil, Vania Dimitrova and Dhavalkumar Thakker, proposing personalized nudges to help users explore linked data graphs, to identify user's familiarity in a domain, using basic level concepts in a linked data graph ,which, given the growth of semantic web data, may have long term implications for domains out with the linked-‐data world; social web-‐inspired research, such as the paper "Detecting Filter Bubbles in Ongoing News Stories" by Giang Binh Tran and Eelco Herder, describing preliminary work on timeline summarisation and prediction in the news area, allowing for identification of differences between timelines from different sources about the same story; less-‐explored user modelling features, such as emotions, in the paper "Personality & Emotional States: Understanding Users' Music Listening Needs" by Bruce Ferwerda, Markus Schedl and Marko Tkalcic, representing an exploration of emotional patterns in music preferences based on large user studies, which represents a starting point for the design of music recommender systems; important application-‐oriented research, such as health, in the paper "What's On My Plate: Towards Recommending Recipe Variations for Diabetes Patients" by Markus Rokicki, Eelco Herder and Elena Demidova, giving preliminary insights into features of a recipe dataset clustered based on dishes, and aimed at extracting dietary patterns of specific communities, such as people affected by diabetes, as a starting point for a needs-‐based recipe recommendation system, followed by the paper "Adaptive Recommendations for Patients with Diabetes" by Stephan Weibelzahl, Dominikus Heckmann, Eelco Herder, Karsten Müssig and Janko Schildt, giving concrete project ideas about a personalised system for diabetes patients, supporting patients in making decision that are related to the treatment, by modelling their behaviour and their physiology. We thank all authors for submitting and presenting their works, and members of the Program Committee for providing their valuable time and expertise for reviewing and selecting the papers. All their efforts made UMAP 2015 late-‐breaking results possible.
University of British Columbia University of Leeds Johannes Kepler University Department of Computational Perception KMI, TU-Graz LinkedIn Corporation Private University of Applied Sciences Göttingen Alpen-Adria-Universitaet Klagenfurt Nanyang Technological University DePaul University