@inproceedings{ubo_mods_00191230, author = {Ma, Yuan and Kleemann, Timm and Ziegler, Jürgen}, editor = {}, title = {Psychological User Characteristics and Meta-Intents in a Conversational Product Advisor}, booktitle = {Proceedings of the 9th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems}, series = {CEUR Workshop Proceedings}, year = {2022}, publisher = {}, address = {}, volume = {3222}, pages = {18–32}, keywords = {conversational UI design, interactive behavior analysis, decision making, influence of psychological factors on interaction}, abstract = {We present a study investigating psychological characteristics of users of a GUI-style conversational recommender system in a real-world application case. We collected data of 496 customers of an online shop using a conversational product advisor (CPA), using questionnaire responses concerning decision- making style and a set of meta-intents, a concept we propose to represent high-level user preferences related to the decision process in a CPA. We also analyzed anonymized data on users’ interactions in the CPA. Concerning general decision-making style, we could identify two clusters of users who differ in their scores on scales measuring rational and intuitive decision-making. We found evidence that rationality and intuitiveness scores are differently correlated with the proposed meta-intents such as efficiency orientation, interest in detail, and openness for guidance. Relations with interaction data could be observed between rationality/intuitiveness scores and overall time spent in the CPA. Trying to classify users’ decision style from their interactions, however did not yield positive results. Despite the limitation that only a single CPA was studied in a single domain, our results provide evidence that the proposed meta-intents are linked to the general decision-making style of a user and can thus be instrumental in translating general decision-making factors into more concrete design guidance for CPA and their potential personalization.}, issn = {1613-0073}, url = {http://ceur-ws.org/Vol-3222/paper2.pdf}, language = {en} } @inproceedings{ubo_mods_00167689, author = {Kleemann, Timm and Wagner, Magdalena and Loepp, Benedikt and Ziegler, Jürgen}, title = {Modeling User Interaction at the Convergence of Filtering Mechanisms, Recommender Algorithms and Advisory Components}, booktitle = {Mensch Und Computer 2021 – Tagungsband}, year = {2021}, publisher = {ACM}, address = {New York, NY, USA}, pages = {531–543}, keywords = {Human factors; User experience; User modeling; Search interfaces; Recommender systems}, isbn = {978-1-4503-8645-6}, doi = {10.1145/3473856}, url = {https://dl.acm.org/doi/10.1145/3473856.3473859?cid=87958660357}, language = {en}, abstract = {A variety of methods is used nowadays to reduce the complexity of product search on e-commerce platforms, allowing users, for example, to specify exactly the features a product should have, but also, just to follow the recommendations automatically generated by the system. While such decision aids are popular with system providers, research to date has mostly focused on individual methods rather than their combination. To close this gap, we propose to support users in choosing the right method for the current situation. As a first step, we report in this paper a user study with a fictitious online shop in which users were able to flexibly use filter mechanisms, rely on recommendations, or follow the guidance of a dialog-based product advisor. We show that from the analysis of the interaction behavior, a model can be derived that allows predicting which of these decision aids is most useful depending on the user’s situation, and how this is affected by demographics and personality.} } @inproceedings{ubo_mods_00167688, author = {Loepp, Benedikt}, title = {On the Convergence of Intelligent Decision Aids}, booktitle = {Mensch Und Computer 2021 – Workshopband}, year = {2021}, publisher = {Gesellschaft für Informatik e.V.}, address = {Bonn}, keywords = {Decision support; Human factors; Information filtering; Adaptive systems; Recommender systems; User experience; User modeling}, abstract = {On the one hand, users’ decision making in today’s web 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.}, doi = {10.18420/muc2021-mci-ws02-371}, url = {https://doi.org/10.18420/muc2021-mci-ws02-371}, language = {en} } @inproceedings{ubo_mods_00154819, author = {Kunkel, Johannes and Schwenger, Claudia and Ziegler, Jürgen}, title = {NewsViz: Depicting and Controlling Preference Profiles Using Interactive Treemaps in News Recommender Systems}, booktitle = {UMAP 2020 - Proceedings of the 28th ACM Conference on User Modeling, Adaptation and Personalization}, year = {2020}, publisher = {Association for Computing Machinery (ACM)}, address = {New York}, pages = {126–135}, keywords = {treemaps}, abstract = {News articles are increasingly consumed digitally and recommender systems (RS) are widely used to personalize news feeds for their users. Thereby, particular concerns about possible biases arise. When RS filter news articles opaquely, they might "trap" their users in filter bubbles. Additionally, user preferences change frequently in the domain of news, which is challenging for automated RS. We argue that both issues can be mitigated by depicting an interactive version of the user’s preference profile inside an overview of the entire domain of news articles. To this end, we introduce NewsViz, a RS that visualizes the domain space of online news as treemap, which can interactively be manipulated to personalize a feed of suggested news articles. In a user study (N=63), we compared NewsViz to an interface based on sliders. While both prototypes yielded high results in terms of transparency, recommendation quality and user satisfaction, NewsViz outperformed its counterpart in the perceived degree of control. Structural equation modeling allows us to further uncover hitherto underestimated influences between quality aspects of RS. For instance, we found that the degree of overview of the item domain influenced the perceived quality of recommendations.}, isbn = {9781450368612}, doi = {10.1145/3340631.3394869} } @inproceedings{ubo_mods_00138306, author = {Kunkel, Johannes and Feldkamp, Tamara and Ziegler, Jürgen}, title = {Kartenbasierte Produktraumdarstellung zur Erhöhung von Transparenz und Steuerbarkeit in Empfehlungssystemen}, booktitle = {Mensch und Computer 2019: Tagungsband}, year = {2019}, publisher = {ACM}, address = {New York}, keywords = {Filterblasen}, note = {Poster Abstract}, doi = {10.1145/3340764.3344893}, abstract = {Empfehlungssysteme (ES) werden häufig eingesetzt, um Nutzer bei der Auswahl eines Produkts aus vielen Alternativen zu unterstützen. Während Empfehlungsalgorithmen hinsichtlich ihrer Präzision bereits sehr ausgereift sind, verhindern mangelnde Transparenz der Empfehlungen und fehlende Interaktionsmöglichkeiten, dass ES ihr volles Potential entfalten. In diesem Beitrag stellen wir eine Methode vor, die einerseits auf verständlichere Empfehlungen und mehr Kontrolle durch den Nutzern abzielt, andererseits aber auch dessen Übersicht über die Produktdomäne adressiert. Dabei dient eine Verteilung aller Produkte auf einer zweidimensionalen Fläche als Basis. Innerhalb können Nutzer ihre Präferenzen ausdrücken, woraufhin das ES mit passenden Empfehlungen reagiert. Um die Empfehlungen zu verändern, können Nutzer ihre Präferenzen anpassen, was in einem kontinuierlichen Feedback-Zyklus zwischen Nutzer und ES resultiert. Die Methode wird zudem an zwei Prototypen demonstriert, welche sie in verschiedenen Produktdomänen und mit unterschiedlichen Formen der Visualisierung und Interaktion umsetzen. Empirische Nutzerstudien zu den Prototypen versprechen ein hohes Potential des Ansatzes Übersicht, Transparenz und Kontrolle in ES zu verbessern.} } @inproceedings{Kunkel.2019b, author = {Kunkel, Johannes and Ziegler, Jürgen}, title = {Visualizing Item Spaces to Increase Transparency and Control in Recommender Systems}, booktitle = {AI and HCI Workshop at CHI’19}, year = {2019} } @inproceedings{ubo_mods_00117943, author = {Kizina, Anna and Kunkel, Johannes and Ziegler, Jürgen}, title = {Ein kollaboratives Task-Management-System mit spielerischen Elementen}, booktitle = {Mensch und Computer 2018: Workshopband}, year = {2018}, publisher = {Gesellschaft für Informatik e.V.}, address = {Bonn}, keywords = {Kollaboration}, issn = {2510-2672}, doi = {10.18420/muc2018-ws03-0477} } @inproceedings{ubo_mods_00116350, author = {Barbu, Catalin-Mihai and Ziegler, Jürgen}, editor = {Neidhardt, Julia and Wörndl, Wolfgang and Kuflik, Tsvi and Zanker, Markus}, title = {Designing Interactive Visualizations of Personalized Review Data for a Hotel Recommender System}, booktitle = {RecTour 2018: 3rd Workshop on Recommenders in Tourism co-located with the 12th ACM Conference on Recommender Systems (RecSys 2018)}, series = {CEUR Workshop Proceedings}, year = {2018}, publisher = {RWTH}, address = {Aachen}, volume = {2222}, pages = {7–12}, keywords = {Tourism}, abstract = {Online reviews extracted from social media are being used increasingly in recommender systems, typically to enhance prediction accuracy. A somewhat less studied avenue of research aims to investigate the underlying relationships that arise between users, items, and the topics mentioned in reviews. Identifying these–often implicit–relationships could be beneficial for at least a couple of reasons. First, they would allow recommender systems to personalize reviews based on a combination of both topic and user similarity. Second, they can facilitate the development of novel interactive visualizations that complement and help explain recommendations even further. In this paper, we report on our ongoing work to personalize user reviews and visualize them in an interactive manner, using hotel recommending as an example domain. We also discuss several possible interactive mechanisms and consider their potential benefits towards increasing users’ satisfaction.}, issn = {1613-0073}, url = {http://ceur-ws.org/Vol-2222/paper2.pdf} } @inproceedings{ubo_mods_00106122, author = {Kunkel, Johannes and Donkers, Tim and Barbu, Catalin-Mihai and Ziegler, Jürgen}, booktitle = {2nd Workshop on Theory-Informed User Modeling for Tailoring and Personalizing Interfaces (HUMANIZE)}, title = {Trust-Related Effects of Expertise and Similarity Cues in Human-Generated Recommendations}, year = {2018}, keywords = {Structural Equation Modeling}, url = {http://ceur-ws.org/Vol-2068/humanize5.pdf}, abstract = {A user’s trust in recommendations plays a central role in the acceptance or rejection of a recommendation. One factor that influences trust is the source of the recommendations. In this paper we describe an empirical study that investigates the trust-related influence of social presence arising in two scenarios: human-generated recommendations and automated recommending. We further compare visual cues indicating the expertise of a human recommendation source and its similarity with the target user, and evaluate their influence on trust. Our analysis indicates that even subtle visual cues can signal expertise and similarity effectively, thus influencing a user’s trust in recommendations. These findings suggest that automated recommender systems could benefit from the inclusion of social components–especially when conveying characteristics of the recommendation source. Thus, more informative and persuasive recommendation interfaces may be designed using such a mixed approach.} } @inproceedings{ubo_mods_00094630, author = {Barbu, Catalin-Mihai and Ziegler, Jürgen}, editor = {Boratto, Ludovico and Carta, Salvatore and Fenu, Gianni}, chapter = {}, title = {Towards a Design Space for Personalizing the Presentation of Recommendations}, series = {CEUR workshop proceedings}, year = {2017}, volume = {1945}, pages = {10–17}, keywords = {Interactive control}, url = {http://ceur-ws.org/Vol-1945/paper_3.pdf}, abstract = {Although personalization plays a major role in the development of recommender systems, the presentation of recommendations and especially the way in which it can be adapted to suit the user’s needs has received relatively little attention from the research community. We introduce a design space for personalizing the presentation of recommendations and propose several dimensions that should be a part of it. Moreover, we present our initial insights about possible interactive mechanisms as well as potential evaluation criteria. Our goal is to provide a systematic way of designing personalized recommendation content, which should prove benecial for other researchers working on this topic. In the longer term, we are interested to investigate whether such personalized presentation implementations influence the perceived trustworthiness of the recommendations.}, booktitle = {EnCHIReS 2017: Engineering Computer-Human Interaction in Recommender Systems : Proceedings of the Second Workshop on Engineering Computer-Human Interaction in Recommender Systems co-located with the 9th ACM SIGCHI Symposium on Engineering Interactive Computing Systems (EICS 2017)} } @inproceedings{ubo_mods_00092173, author = {Biefang, Kai and Kunkel, Johannes and Loepp, Benedikt and Ziegler, Jürgen}, chapter = {}, title = {Eine Sandbox zur physisch-virtuellen Exploration von Ausgrabungsstätten}, year = {2017}, publisher = {Gesellschaft für Informatik}, keywords = {Archäologie}, doi = {10.18420/muc2017-demo-0300}, url = {https://dl.gi.de/handle/20.500.12116/3248}, abstract = {In diesem Beitrag stellen wir die Archäologische Sandbox vor: Ein Tangible User Interface (TUI) mit dem archäologische Ausgrabungsstätten und dort gefundene Artefakte exploriert werden können. Das System zielt auf den Einsatz in Museen ab, die ihren Besuchern den Zusammenhang von ausgestellten Exponaten und der Ausgrabungsstätte näherbringen möchten, an der diese gefunden wurden. Den Kern des TUIs bildet eine mit Sand gefüllte Box, auf dessen Oberfläche eine geografische Karte projiziert wird. Durch das Graben im Sand an der richtigen Stelle werden Informationen zu an diesem Ort gefundenen Ausstellungsstücken abgerufen. Eine durchgeführte qualitative Interviewstudie bestätigt die intuitive Bedienbarkeit und die intrinsisch motivierenden Interaktionsmöglichkeiten des Systems.}, booktitle = {Mensch und Computer 2017 – Workshopband} } @inproceedings{ubo:69423, author = {Gaulke, Werner and Ziegler, Jürgen}, chapter = {}, title = {Rule-enhanced task models for increased expressiveness and compactness}, year = {2016}, edition = {EICS ’16}, publisher = {ACM}, address = {Brussels, Belgium}, pages = {4–15}, isbn = {978-1-4503-4322-0}, doi = {10.1145/2933242.2933243}, abstract = {User centered design and development of interactive systems utilizes theoretically well-grounded, yet practical ways to capture user’s goals and intentions. Task models are an established approach to break down a central objective into a set of hierarchical organized tasks. While task models achieve to provide a good overview of the overall system, they often lack detail necessary to (semi-) automatically generate user interfaces. Based on requirements derived from a comprehensive overview of existing task model extensions, improvements and development methods, an approach that integrates logical rules with task models is introduced. By means of practical examples it is shown, that the integration of rules enables advanced execution flows as well as leaner task models thus improving their practical value.}, booktitle = {Proceedings of the 8th ACM SIGCHI Symposium on Engineering Interactive Computing Systems} } @article{ubo:22487, author = {Niesenhaus, Jörg}, title = {Challenges and Potentials of User Involvement in the Process of Creating Games}, journal = {International Reports on Socio-Informatics: Open Design Spaces Supporting User Innovation}, year = {2009}, volume = {2/2009}, number = {volume 6}, pages = {56–68}, abstract = {This article gives a short overview about the history of user involvement in the area of digital games and describes the speci?c challenges and potentials of the participation and motivation of users in this application area. It speci?es the different degrees and types of user involvement and outlines the current state of the art. Moreover, the article discusses the implications of user involvement for game companies and users with a special regard to user-generated content and gives an outlook on future development.} } @inproceedings{ubo:19284, author = {Lohmann, Steffen and Ziegler, Jürgen and Heim, Philipp}, editor = {Forbrig, Peter and Paternò, Fabio}, chapter = {}, title = {Involving End Users in Distributed Requirements Engineering}, year = {2008}, publisher = {Springer}, address = {Berlin, Heidelberg}, abstract = {Active involvement of end users in the development of interactive systems is both highly recommended and highly challenging. This is particularly true in settings where the requirements of a large number of geographically distributed users have to be taken into account. In this paper, we address this problem by introducing an integrated, web-based approach that enables users to easily express their ideas on how the interaction with a system could be improved. In addition, the user input is contextualized, allowing for highly structured means to access, explore, and analyze the user requirements.}, isbn = {9783540859918}, booktitle = {Engineering Interactive Systems 2008} }