UMAP_latebreaking'15 Accepted Papers with Abstracts
  Bruce Ferwerda,Markus Schedl and Marko Tkalcic

Personality & Emotional States:
Understanding Users' Music Listening Needs


Music plays an important part in people's lives to regulate their emotions throughout the day. We conducted an online user study to investigate how the emotional state relates to the use of emotionally laden music. We found among 359 participants that they in general prefer emotionally laden music that correspond with their emotional state. However, when looking at personality traits, different patterns emerged. We found that when in a negative emotional state, those who scored high on openness, extraversion, and agreeableness tend to cheer themselves up with happy music, while those who scored high on neuroticism tend to increase their worry with sad music. With our results we show general patterns of music usage, but also individual differences. Our results contribute to the improvement of applications such as recommender systems in order to provide tailored recommendations based on users' personality and emotional state.

Giang Binh Tran and Eelco Herder.

Detecting Filter Bubbles in Ongoing News Stories


In this paper, we analyze differences in perspective between timelines created by news agencies from various countries. By employing methods for date and headline selection, which have been extensively evaluated in previous work, we show several types of bias that exist in the media landscape. As users typically select only a small number of news sources to follow, they necessarily experience at least some `tunnel vision', as commonly associated with the so-called `filter bubble'. By recognizing and emphasizing the peculariaties of the users' self-selected news sources, we can help them to break out of the bubble.

Markus Rokicki, Eelco Herder and Elena Demidova.

What's On My Plate:
Towards Recommending Recipe Variations for Diabetes Patients


As community-based recipe platforms continue to grow in popularity, recipe recommendation is an active research area. Simultaneously, the analysis of online recipes can provide us with insights on dietary patterns in particular communities. In this paper, we focus on recipe recommendation for a user group that is relatively contrained in terms of choices: diabetes patients need to balance their diet more than average persons, and need to be aware of the nutritional value of their meals. In this paper, we discuss the type of situations where diabetes-specific food recommendations are desirable. Further, we show how people's age and gender interact with their food intake. Based on a large dataset, we explore how variations in recipes for `canonical meals' can be exploited for recommending which alternatives better fit the user's dietary requirements.

Stephan Weibelzahl, Dominikus Heckmann, Eelco Herder, Karsten Müssig and Janko Schildt.

Adaptive Recommendations for Patients with Diabetes


Diabetes mellitus is a major epidemic with about 8.3% of the world population being affected. Proper treatment minimizes the risk of secondary diseases. The GlycoRec system aims to support patients in making decision that are related to the treatment by modeling their behavior and their physiology. Here we describe the aims and first steps towards the development of GlycoRec.

Marwan Al-Tawil, Vania Dimitrova and Dhavalkumar Thakker.

Using Basic Level Concepts in a Linked Data Graph to Detect User's Domain Familiarity


We investigate how to provide personalized nudges to aid a user’s exploration of linked data in a way leading to expanding her domain knowledge. This requires a model of the user’s familiarity with domain concepts. The paper examines an approach to detect user domain familiarity by exploiting anchoring concepts which provide a backbone for probing interactions over the linked data graph. Basic level concepts studied in Cognitive Science are adopted. A user study examines how such concepts can be utilized to deal with the cold start user modelling problem, which informs a probing algorithm.

Joseph Jay Williams and Neil Heffernan.

A Methodology for Discovering how to Adaptively Personalize to Users using Experimental Comparisons


We explain and provide examples of a formalism that supports the methodology of discovering how to adapt and personalize technology by combining randomized experiments with variables associated with user models. We characterize a formal relationship between the use of technology to conduct A/B experiments and use of technology for adaptive personalization. The MOOClet Formalism [7] captures the equivalence between experimentation and personalization in its conceptualization of modular components of a technology. This motivates a unified software design pattern that enables technology components that can be compared in an experiment to also be adapted based on contextual data, or personalized based on user characteristics. With the aid of a concrete use case, we illustrate the potential of the MOOClet formalism for a methodology that uses randomized experiments of alternative micro-designs to discover how to adapt technology based on user characteristics, and then dynamically implements these personalized improvements in real time.

    Late Breaking Dates
  • Submission Deadline: 18th May 2015
  • Notification to Authors: 29th May 2015
  • Camera Ready Submission: 12th June 2015
    Consortium Dates
  • Extended Submission Deadline: 13th March 2015
  • Notification to Authors: 27th March 2015
  • Camera Ready Submission: 5th April 2015
    Themes and Tracks Dates
  • Abstract Submission: 30th January 2015
  • Paper Submission: 9th February 2015
  • Notification to Authors: 23rd March 2015
  • Camera Ready Submission: 13th April 2015
  • Early Registration Deadline: 3rd May, 2015
  • Late Registration Deadline: 28th June, 2015
  • Submission Times: 11:59pm Hawaii time
    Poster and Demonstration Dates
  • Paper Deadline: 6th April 2015
  • Notification to Authors: 1st May 2015
  • Camera Ready Submission: 15th May 2015
    Tutorials Dates
  • Submission Deadline: 18th May 2015
  • Notification to Authors: 29th May 2015
  • Camera Ready Submission: 12th June 2015