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Auflistung nach Schlagwort "Recommender systems"

1 - 8 von 8
  • Workshopbeitrag
    Argumentative explanations for recommendations - Effect of display style and profile transparency
    (Mensch und Computer 2020 - Workshopband, 2020) Hernandez-Bocanegra, Diana Carolina; Ziegler, Jürgen
    Providing explanations based on user reviews in recommender systems may increase users’ perception of transparency. However, little is known about how these explanations should be presented to users in order to increase both their understanding and acceptance. We present in this paper a user study to investigate the effect of different display styles (visual and text only) on the perception of review-based explanations for recommended hotels. Additionally, we also aim to test the differences in users’ perception when providing information about their own profiles, in addition to a summarized view on the opinions of other users about the recommended hotel. Our results suggest that the perception of explanations regarding these aspects may vary depending on user characteristics, such as decision-making styles or social awareness.
  • Zeitschriftenartikel
    Explaining Review-Based Recommendations: Effects of Profile Transparency, Presentation Style and User Characteristics
    (i-com: Vol. 19, No. 3, 2021) Hernandez-Bocanegra, Diana C.; Ziegler, Jürgen
    Providing explanations based on user reviews in recommender systems (RS) may increase users’ perception of transparency or effectiveness. However, little is known about how these explanations should be presented to users, or which types of user interface components should be included in explanations, in order to increase both their comprehensibility and acceptance. To investigate such matters, we conducted two experiments and evaluated the differences in users’ perception when providing information about their own profiles, in addition to a summarized view on the opinions of other customers about the recommended hotel. Additionally, we also aimed to test the effect of different display styles (bar chart and table) on the perception of review-based explanations for recommended hotels, as well as how useful users find different explanatory interface components. Our results suggest that the perception of an RS and its explanations given profile transparency and different presentation styles, may vary depending on individual differences on user characteristics, such as decision-making styles, social awareness, or visualization familiarity.
  • Zeitschriftenartikel
    Matrix- and Tensor Factorization for Game Content Recommendation
    (KI - Künstliche Intelligenz: Vol. 34, No. 1, 2020) Sifa, Rafet; Yawar, Raheel; Ramamurthy, Rajkumar; Bauckhage, Christian; Kersting, Kristian
    Commercial success of modern freemium games hinges on player satisfaction and retention. This calls for the customization of game content or game mechanics in order to keep players engaged. However, whereas game content is already frequently generated using procedural content generation, methods that can reliably assess what kind of content suits a player’s skills or preferences are still few and far between. Addressing this challenge, we propose novel recommender systems based on latent factor models that allow for recommending quests in a single player role-playing game. In particular, we introduce a tensor factorization algorithm to decompose collections of bipartite matrices which represent how players’ interests and behaviors change over time. Extensive online bucket type tests during the ongoing operation of a commercial game reveal that our system is able to recommend more engaging quests and to retain more players than previous handcrafted or collaborative filtering approaches.
  • Workshopbeitrag
    On the Convergence of Intelligent Decision Aids
    (Mensch und Computer 2021 - Workshopband, 2021) Loepp, Benedikt
    On the one hand, users’ decisionmaking in today’sweb is supported in numerous ways, with mechanisms ranging from manual search over automated recommendation to intelligent advisors. The focus on algorithmic accuracy, however, is questioned more and more. On the other hand, although the boundaries between the mechanisms are blurred increasingly, research on user-related aspects is still conducted separately in each area. In this position paper, we present a research agenda for providing a more holistic solution, in which users are supported with the right decision aid at the right time depending on personal characteristics and situational needs.
  • Zeitschriftenartikel
    Process Modeling Recommender Systems - A Generic Data Model and Its Application to a Smart Glasses-based Modeling Environment
    (Business & Information Systems Engineering: Vol. 60, No. 1, 2018) Fellmann, Michael; Metzger, Dirk; Jannaber, Sven; Zarvic, Novica; Thomas, Oliver
    The manual construction of business process models is a time-consuming, error-prone task and presents an obstacle to business agility. To facilitate the construction of such models, several modeling support techniques have been suggested. However, while recommendation systems are widely used, e.g., in e-commerce, these techniques are rarely implemented in process modeling tools. The creation of such systems is a complex task since a large number of requirements and parameters have to be taken into account. In order to improve the situation, the authors have developed a data model that can serve as a backbone for the development of process modeling recommender systems (PMRS). This article outlines the systematic development of this model in a stepwise approach using established requirements and validates it against a data model that has been reverse-engineered from a real-world system. In a last step, the paper illustrates an exemplary instantiation of the data model in a Smart Glasses-based modeling environment and discusses business process agility issues. The authors expect their contribution to provide a useful starting point for designing the data perspective of process modeling recommendation features that support business agility in process-intensive environments.
  • Zeitschriftenartikel
    School to go: Neues Lernen im Social-Media-Stil
    (HMD Praxis der Wirtschaftsinformatik: Vol. 58, No. 6, 2021) Eckle, Jannick; Jungfleisch, Anne; Stattkus, Daniel; Zarvić, Novica; Knopf, Julia; Thomas, Oliver
    Mit dem pandemiebedingten ersten Lockdown im März 2020 hat das digitale Lernen einen enormen Aufschwung erfahren. Mit der Initiative „School to go“ wird in Zeiten bundesweiter Schulschließungen ein relevanter Beitrag zur digitalen Bildung für Schülerinnen und Schüler, Eltern, Lehrkräfte und die interessierte Öffentlichkeit geleistet. Auf der gleichnamigen Plattform ( www.schooltogo.de ) werden digitale Lernangebote für Kinder, Jugendliche sowie junge Erwachsene gebündelt. Ferner finden sich dort Blogbeiträge zu Trendthemen der digitalen Bildung: Wie können digitale und didaktisch motivierte Raumkonzepte zu einem verbesserten Lernen beitragen und welche Bedeutung hat Gamification für die Lernmotivation der Schülerinnen und Schüler? Derzeit befinden sich auf „School to go“ bereits über 1000 innovative Lernformate (Stand Mai 2021) für verschiedene Fächer, die sich an Schülerinnen und Schüler aller Alters- und Jahrgangsstufen richten. Der vorliegende Beitrag zeigt, wie neues Lernen im Zeitalter der Digitalisierung gelingt und wie hierbei Didaktik und Wirtschaftsinformatik in Einklang gebracht werden können, um nachhaltige Lernerlebnisse zu ermöglichen. With the pandemic-related first lockdown in March 2020, digital learning has experienced a tremendous boost. In times of nationwide school closures, the “School to go” initiative makes a relevant contribution to digital education for students, parents, teachers and the interested public. The platform of the same name ( www.schooltogo.de ) bundles digital learning opportunities for children, young people and young adults. It also features blog posts on trend topics in digital education: How can digital and didactically motivated spatial concepts contribute to improved learning and what significance does gamification have for students’ motivation to learn? Currently, there are already over 1000 innovative learning formats (as of May 2021) for various subjects on “School to go”, aimed at students of all ages and grades. This article shows how new learning succeeds in the age of digitization and how didactics and business informatics should be harmonized to provide sustainable learning experiences.
  • Konferenzbeitrag
    Towards Complex User Feedback and Presentation Context in Recommender Systems
    (Datenbanksysteme für Business, Technologie und Web (BTW 2017) - Workshopband, 2017) Peska, Ladislav; Vojtas, Peter
    In this paper, we present our work in progress towards employing complex user feedback and its context in recommender systems. Our work is generally focused on small or medium-sized e-commerce portals. Due to the nature of such enterprises, explicit feedback is unavailable, but implicit feedback can be collected in both large amount and rich variety. However, some perceived values of implicit feedback may depend on the context of the page or user’s device (further denoted as presentation context). In this paper, we present an extended model of presentation context, propose methods integrating it into the set of implicit feedback features and evaluate these on the dataset of real e-commerce users. The evaluation corroborated the importance of leveraging presentation context in recommender systems.
  • Konferenzbeitrag
    Towards Context-aware Recommender Systems for Supporting Knowledge Workers in Personal and Corporate Information Space
    (INFORMATIK 2024, 2024) Bakhshizadeh, Mahta; Jilek, Christian; Maus, Heiko; Dengel, Andreas
    Although recommender systems have been impressively progressing in many domains, their usage in supporting knowledge workers has not been explored as much as in other applications. Having the existing challenges and the recent studies addressing this novel application introduced, this paper provides a framework for integrating such systems into existing concepts and technologies for knowledge assistance. As a case study, a sample recommendation scenario according to the proposed framework is simulated on the historical data of a small group of knowledge workers. The collected explicit feedback of participants on the made recommendations from both their personal and corporate information space indicate that while the approach is promising (with 54% accuracy in recommending relevant information items), there is still considerable potential for improvement in filtering out noise and better modeling user contexts and information needs.