Now showing items 1-18 of 18

  • Acquiring user profiles from implicit feedback in a conversational recommender system 

    Blanco H; Ricci F (ACM, 2013)
    Query revisions in a conversational system can be efficiently computed by assuming that the profiles of the potential users are in a predefined, a priori known and finite set. However, without any additional knowledge of ...
  • Assessing the Threat of Untracked Changes in Software Evolution 

    Hora A; Silva D; Valente MT; Robbes R (ACM, 2018)
    While refactoring is extensively performed by practitioners, many Mining Software Repositories (MSR) approaches do not detect nor keep track of refactorings when performing source code evolution analysis. In the best case, ...
  • Computing isochrones in multi-modal, schedule-based transport networks 

    Bauer, V; Gamper, J; Loperfido, R; Profanter, S; Putzer, S; Timko, I (Curran, 2008)
    Isochrones are defined as the set of all points from which a specific point of interest is reachable within a given time span. This demo paper presents a solution to compute isochrones in multi-modal, schedule-based transport ...
  • The evolving design of tangibles for graph algorithmic thinking 

    Bonani A; Del Fatto V; Gennari R (Association for Computing Machinery, Inc, 2018)
    Algorithmic thinking is at the core of computational thinking. Tangible interactive solutions can help children develop algorithmic thinking skills. This paper focusses on exploratory research concerning tangibles for graph ...
  • Optimizing Update Frequencies for Decaying Information 

    Razniewski S (ACM, 2016)
    Many kinds of information, e.g., addresses, crawls of webpages, or academic affiliations, are prone to becoming outdated over time. Therefore, if data quality shall be maintained over time, often periodical refreshing is ...
  • Personality Traits Predict Music Taxonomy Preferences 

    Ferwerda B; Yang E; Schedl M; Tkalcic M (ACM, 2015)
    Music streaming services increasingly incorporate additional music taxonomies (i.e., mood, activity, and genre) to provide users different ways to browse through music collections. However, these additional taxonomies can ...
  • Predicting Personality Traits with Instagram Pictures 

    Ferwerda B; Schedl M; Tkalcic M (ACM, 2015)
    Instagram is a popular social networking application, which allows photo-sharing and applying different photo filters to adjust the appearance of a picture. By applying photo filters, users are able to create a style that ...
  • Preface: EMPIRE 2015 - 3rd workshop on emotions and personality in personalized services 

    Tkalčič M; De Carolis B; De Gemmis M; Odić A; Košir A (Association for Computing Machinery, 2015)
    The 3rd Workshop on Emotions and Personality in Personalized Systems (EMPIRE) is taking place in Vienna on September 19th, 2015 in conjunction with the ACM RecSys 2015 conference. The workshop focuses on the acquisition ...
  • Profiling call changes via motif mining 

    Russo B (ACM, 2018)
    Components' interactions in software systems evolve over time increasing in complexity and size. Developers might have hard time to master such complexity during their maintenance activities incrementing the risk to make ...
  • Situation-dependent combination of long-term and session-based preferences in group recommendations: an experimental analysis 

    Nguyen TN; Ricci F (ACM, 2018)
    A major challenge for conversational group recommender systems is how to properly exploit the user's preferences induced by the interactions between group members, which may deviate from the user's long-term ones. We argue ...
  • Tailoring training for obese individuals with case-based reasoning 

    Lorenzi F; Dorneles G; Da Rosa R; Peres A; Ricci F (Association for Computing Machinery, Inc, 2017)
    Obesity is a complex disease that involves genetic factors, inflammatory patterns, resilience and psycho-social factors. An effective system which is able to recommend adequate training for obese subjects that starts a new ...
  • Towards a deep learning model for hybrid recommendation 

    Sottocornola G; Stella F; Zanker M; Canonaco F (ACM, 2017)
    The deep learning wave is propagating through many research areas and communities. In the last years it quickly propagated to Recommendation Systems, a research area which aims to recommend items to users. Indeed, many ...
  • UMAP 2017 Workshop on Surprise, Opposition, and Obstruction in Adaptive and Personalized Systems: Organizers' welcome 

    Knees P; Andersen K; Said A; Tkalcic M (ACM, 2017)
    It is our great pleasure to welcome you to the UMAP 2017 Workshop on Surprise, Opposition, and Obstruction in Adaptive and Personalized Systems (SOAP). Following the successful first edition of the workshop at UMAP 2016, ...
  • UMAP'17 Late-Breaking Results, Demonstration and Theory, Opinion & Reflection Papers Chairs' Preface 

    Tkalcic M; Thakker D (ACM, 2017)
    It is our great pleasure to welcome you to the UMAP 2017 LBR, Demo, and TOR Track, the 25th User Modelling, Adaptation and Personalization, held in Bratislava, Slovakia organized between the July 9-12th, 2017. This track ...
  • User behaviour analysis in a simulated IoT augmented space 

    Massimo D; Not E; Ricci F (ACM, 2018)
    In this paper we present a demo application aimed at supporting the research in the field of tourism and mobility support in IoT augmented areas. The application collects tourists’ choices while browsing Points of Interest ...
  • User Nutrition Modelling and Recommendation: Balancing Simplicity and Complexity 

    Schäfer H; Elahi M; Elsweiler D; Groh G; Harvey M; Ludwig B; Ricci F; Said A (ACM, 2017)
    In order to use and model nutritional knowledge in a food recommender system, uncertainties regarding the users nutritional state and thus the personal health value of food items, as well as conflicting nutritional theories ...
  • VISOR: Visualizing Summaries of Ordered Data 

    Mahlknecht G; Böhlen M; Dignös A; Gamper J (ACM, 2017)
    In this paper, we present the VISOR tool, which helps the user to explore data and their summary structures by visualizing the relationships between the size k of a data summary and the induced error. Given an ordered ...
  • Visual Analysis of Recommendation Performance 

    Çoba L; Symeonidis P; Zanker M (ACM, 2017)
    Rrecsys is a novel library in R for developing and assessing recommendation algorithms. In this demo, we extend rrecsys with functions for visual analytics of recommendation performance, that is one of the strong capabilities ...