@inproceedings{loepp2023how, author = {Loepp, Benedikt and Ziegler, Jürgen}, booktitle = {RecSys ’23: Proceedings of the 17th ACM Conference on Recommender Systems}, title = {How Users Ride the Carousel: Exploring the Design of Multi-List Recommender Interfaces From a User Perspective}, year = {2023}, address = {New York, NY, USA}, publisher = {ACM}, isbn = {9798400702419}, url = {https://doi.org/10.1145/3604915.3610638}, doi = {10.1145/3604915.3610638}, abstract = {Multi-list interfaces are widely used in recommender systems, especially in industry, showing collections of recommendations, one below the other, with items that have certain commonalities. The composition and order of these "carousels" are usually optimized by simulating user interaction based on probabilistic models learned from item click data. Research that actually involves users is rare, with only few studies investigating general user experience in comparison to conventional recommendation lists. Hence, it is largely unknown how specific design aspects such as carousel type and length influence the individual perception and usage of carousel-based interfaces. This paper seeks to fill this gap through an exploratory user study. The results confirm previous assumptions about user behavior and provide first insights into the differences in decision making in the presence of multiple recommendation carousels.} } @inproceedings{ubo_mods_00191514, author = {Loepp, Benedikt}, title = {Recommender Systems Alone Are Not Everything: Towards a Broader Perspective in the Evaluation of Recommender Systems}, booktitle = {PERSPECTIVES ’22: Proceedings of the 2nd Workshop on Perspectives on the Evaluation of Recommender Systems}, year = {2022}, abstract = {Thus far, in most of the user experiments conducted in the area of recommender systems, the respective system is considered as an isolated component, i.e., participants can only interact with the recommender that is under investigation. This fails to recognize the situation of users in real-world settings, where the recommender usually represents only one part of a greater system, with many other options for users to find suitable items than using the mechanisms that are part of the recommender, e.g., liking, rating, or critiquing. For example, in current web applications, users can often choose from a wide range of decision aids, from text-based search over faceted filtering to intelligent conversational agents. This variety of methods, which may equally support users in their decision making, raises the question of whether the current practice in recommender evaluation is sufficient to fully capture the user experience. In this position paper, we discuss the need to take a broader perspective in future evaluations of recommender systems, and raise awareness for evaluation methods which we think may help to achieve this goal, but have not yet gained the attention they deserve.}, url = {http://ceur-ws.org/Vol-3228/paper5.pdf} } @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_00167803, author = {Ma, Yuan and Kleemann, Timm and Ziegler, Jürgen}, title = {Mixed-Modality Interaction in Conversational Recommender Systems}, booktitle = {Proceedings of the 8th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems}, series = {CEUR Workshop Proceedings}, year = {2021}, publisher = {}, address = {}, volume = {2948}, pages = {21–37}, keywords = {Conversational Recommender Systems; User Interface; Preference Elicitation; Critique-based Recommendations}, abstract = {Recent advances in natural language processing have made modern chatbots and Conversational Recommender Systems (CRS) increasingly intelligent, enabling them to handle more complex user inputs. Still, the interaction with a CRS is often tedious and error-prone. Especially when using written text as the form of conversation, the interaction is often less efficient in comparison to conventional GUI- style interaction. To keep the flexibility and mixed-initiative style of language-based conversation while leveraging the efficiency and simplicity of interacting through graphical widgets, we investigate the de- sign space of integrating GUI elements into text-based conversations. While simple response buttons have already been used in chatbots, the full range of such mixed-modality interactions has not yet been investigated in existing research. We propose two design dimensions along which integrations can be defined and analyze their applicability for preference elicitation and for critiquing the CRS’s responses at different levels. We report a user study in which we investigated user preferences and perceived usability of different techniques based on video prototypes.}, note = {OA platinum}, issn = {1613-0073}, url = {http://ceur-ws.org/Vol-2948/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_00167074, author = {Hernandez-Bocanegra, Diana C. and Ziegler, Jürgen}, title = {Conversational Review-based Explanations for Recommender Systems: Exploring Users’ Query Behavior}, booktitle = {CUI 2021 - 3rd Conference on Conversational User Interfaces}, series = {ACM International Conference Proceeding Series}, year = {2021}, publisher = {Association for Computing Machinery (ACM)}, address = {New York}, keywords = {argumentation; conversational agent; explanations; Recommender systems; user study}, abstract = {Providing explanations based on user reviews in recommender systems (RS) can increase users’ perception of system transparency. While static explanations are dominant, interactive explanatory approaches have emerged in explainable artificial intelligence (XAI), so that users are more likely to examine system decisions and get more arguments supporting system assertions. However, little attention has been paid to conversational approaches for explanations targeting end users. In this paper we explore how to design a conversational interface to provide explanations in a review-based RS, and present the results of a Wizard of Oz (WoOz) study that provided insights into the type of questions users might ask in such a context, as well as their perception of a system simulating such a dialog. Consequently, we propose a dialog management policy and user intents for explainable review-based RS, taking as an example the hotels domain.}, isbn = {9781450389983}, doi = {10.1145/3469595.3469596}, url = {https://dl.acm.org/doi/10.1145/3469595.3469596?cid=99659550942}, language = {en} } @inproceedings{ubo_mods_00166661, author = {Hernandez Bocanegra, Diana Carolina and Ziegler, Jürgen}, editor = {Hansen, C. and Nürnberger, A. and Preim, B.}, title = {Argumentative explanations for recommendations - Effect of display style and profile transparency}, booktitle = {Mensch und Computer 2020}, year = {2020}, keywords = {Recommender systems, explanations, user study}, abstract = {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.}, doi = {10.18420/muc2020-ws111-338}, url = {https://doi.org/10.18420/muc2020-ws111-338}, language = {en} } @inproceedings{ubo_mods_00157832, author = {Álvarez Márquez, Jesús Omar and Ziegler, Jürgen}, title = {In-Store Augmented Reality-Enabled Product Comparison and Recommendation}, booktitle = {14th ACM Conference on Recommender Systems}, year = {2020}, publisher = {Association for Computing Machinery (ACM)}, address = {New York}, pages = {180–189}, keywords = {recommender systems}, isbn = {9781450375832}, doi = {10.1145/3383313.3412266}, abstract = {We present an approach combining the AR-based presentation of product attributes in a physical retail store with recommendations for items only available online. The system supports users’ decision-making process by offering functions for comparing product features between items, both physical and online, and by providing recommendations based on selecting in-store products. The physical products may thus serve as anchors for forming the user’s preferences, also offering a richer and more engaging experience when exploring the products hands-on. Both objective product attributes as well as the visual appearance of a physical product are employed for generating recommendations from the online space. In this way, the advantages of online and in-store shopping can be combined, creating novel multi-channel opportunities for businesses. An empirical evaluation showed that the comparison and recommendation functions were appreciated by users, and hinted some possible benefits of a hybrid physical-online shopping support system. Despite the limitations of the study, there is sufficient evidence to consider this a viable approach worth to be further explored.} } @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_00154785, author = {Naveed, Sidra and Loepp, Benedikt and Ziegler, Jürgen}, title = {On the Use of Feature-based Collaborative Explanations: An Empirical Comparison of Explanation Styles}, booktitle = {ExUM ’20: Proceedings of the International Workshop on Transparent Personalization Methods based on Heterogeneous Personal Data}, year = {2020}, publisher = {ACM}, address = {New York}, pages = {226–232}, keywords = {User Experience}, doi = {10.1145/3386392.3399303}, url = {https://dl.acm.org/doi/10.1145/3386392.3399303?cid=87958660357}, abstract = {Current attempts to explain recommendations mostly exploit a single type of data, i.e. usually either ratings provided by users for items in collaborative filtering systems, or item features in content-based systems. While this might be sufficient in straightforward recommendation scenarios, the complexity of other situations could require the use of multiple datasources, for instance, depending on the product domain. Even though hybrid systems have a long and successful history in recommender research, the connections between user ratings and item features have only rarely been used for offering more informative and transparent explanations. In previous work, we presented a prototype system based on a feature-weighting mechanism that constitutes an exception, allowing to recommend both items and features based on ratings while offering advanced explanations based on content data. In this paper, we empirically evaluate this prototype in terms of user-oriented aspects and user experience against to widely accepted baselines. Two user studies show that our novel approach outperforms conventional collaborative filtering, while a pure content-based system was perceived in a similarly positive light. Overall, the results draw a promising picture, which becomes particularly apparent from a user perspective when participants were specifically asked to use the explanations: they indicated in their qualitative feedback that they understood them and highly appreciated their availability.} } @inproceedings{ubo_mods_00154786, author = {Hernandez-Bocanegra, Diana C. and Donkers, Tim and Ziegler, Jürgen}, title = {Effects of Argumentative Explanation Types on the Perception of Review-Based Recommendations}, booktitle = {Adjunct Proceedings of the 28th ACM Conference on User Modeling, Adaptation and Personalization (UMAP ’20 Adjunct)}, year = {2020}, publisher = {Association for Computing Machinery (ACM)}, address = {New York}, pages = {219–225}, keywords = {user study}, abstract = {Recommender systems have achieved considerable maturity and accuracy in recent years. However, the rationale behind recommendations mostly remains opaque. Providing textual explanations based on user reviews may increase users’ perception of transparency and, by that, overall system satisfaction. However, little is known about how these explanations can be effectively and efficiently presented to the user. In the following paper, we present an empirical study conducted in the domain of hotels to investigate the effect of different textual explanation types on, among others, perceived system transparency and trustworthiness, as well as the overall assessment of explanation quality. The explanations presented to participants follow an argument-based design, which we propose to provide a rationale to support a recommendation in a structured way. Our results show that people prefer explanations that include an aggregation using percentages of other users’ opinions, over explanations that only include a brief summary of opinions. The results additionally indicate that user characteristics such as social awareness may influence the perception of explanation quality.}, isbn = {9781450367110}, doi = {10.1145/3386392.3399302}, url = {https://dl.acm.org/doi/10.1145/3386392.3399302?cid=99659550942} } @inproceedings{ubo_mods_00144402, author = {Loepp, Benedikt and Ziegler, Jürgen}, title = {Measuring the Impact of Recommender Systems – A Position Paper on Item Consumption in User Studies}, booktitle = {Proceedings of the 1st Workshop on Impact of Recommender Systems (ImpactRS ’19)}, year = {2019}, keywords = {User Studies}, url = {https://impactrs19.github.io/papers/short4.pdf}, abstract = {While participants of recommender systems user studies usually cannot experience recommended items, it is common practice that researchers ask them to fill in questionnaires regarding the quality of systems and recommendations. While this has been shown to work well under certain circumstances, it sometimes seems not possible to assess user experience without enabling users to consume items, raising the question of whether the impact of recommender systems has always been measured adequately in past user studies. In this position paper, we aim at exploring this question by means of a literature review and at identifying aspects that need to be further investigated in terms of their influence on assessments in users studies, for instance, the difference between consumption of products or only of related information as well as the effect of domain, domain knowledge and other possibly confounding factors.} } @inproceedings{ubo_mods_00140449, author = {Torkamaan, Helma and Barbu, Catalin-Mihai and Ziegler, Jürgen}, editor = {Bogers, Toine and Said, Alan}, title = {How Can They Know That? A Study of Factors Affecting the Creepiness of Recommendations}, booktitle = {Proceedings of the 13th ACM Conference on Recommender Systems}, year = {2019}, publisher = {ACM}, address = {New York, NY}, pages = {423–427}, keywords = {Trust}, isbn = {978-1-4503-6243-6}, doi = {10.1145/3298689.3346982}, abstract = {Recommender systems (RS) often use implicit user preferences extracted from behavioral and contextual data, in addition to traditional rating-based preference elicitation, to increase the quality and accuracy of personalized recommendations. However, these approaches may harm user experience by causing mixed emotions, such as fear, anxiety, surprise, discomfort, or creepiness. RS should consider users’ feelings, expectations, and reactions that result from being shown personalized recommendations. This paper investigates the creepiness of recommendations using an online experiment in three domains: movies, hotels, and health. We define the feeling of creepiness caused by recommendations and find out that it is already known to users of RS. We further find out that the perception of creepiness varies across domains and depends on recommendation features, like causal ambiguity and accuracy. By uncovering possible consequences of creepy recommendations, we also learn that creepiness can have a negative influence on brand and platform attitudes, purchase or consumption intention, user experience, and users’ expectations of—and their trust in—RS.} } @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{ubo_mods_00139553, author = {Álvarez Márquez, Jesús Omar and Ziegler, Jürgen}, title = {Augmented-Reality-Enhanced Product Comparison in Physical Retailing}, booktitle = {Mensch und Computer 2019: Tagungsband}, year = {2019}, publisher = {ACM Press}, address = {New York}, pages = {55–65}, keywords = {natural interaction}, isbn = {978-1-4503-7198-8}, doi = {10.1145/3340764.3340800}, abstract = {Augmented reality technology has experienced great improvement in recent years and it has been successfully applied to industry and entertainment settings. However, its application in everyday contexts such as shopping is still very limited. One of the requirements to seamlessly incorporate augmented reality into everyday tasks is to find intuitive, natural methods to make use of it. Due to the inherent capabilities of augmented reality to work as a visual aid to explore and extend the knowledge a user has of the surroundings, this paper proposes the combination of AR technology and product advisors in a novel approach for product comparison. The user’s awareness of the differences between multiple physically present objects is enhanced through virtual augmentations, supporting an intuitive way of comparing two or more products while shopping. To assess the validity of the concept, a prototype for an AR-based shopping assistant for comparing vacuum cleaners has been implemented and evaluated in a user study, testing different methods of visual comparison and interaction.} } @inproceedings{ubo_mods_00139552, author = {Kleemann, Timm and Ziegler, Jürgen}, title = {Integration of Dialog-based Product Advisors into Filter Systems}, booktitle = {Proceedings of the Conference on Mensch und Computer}, series = {ACM International Conference Proceeding Series}, year = {2019}, publisher = {ACM Press}, address = {New York}, pages = {67–77}, keywords = {Dialogbasierte Produktberater, Filtersysteme}, isbn = {978-1-4503-7198-8}, doi = {10.1145/3340764.3340786}, abstract = { Different techniques such as search functions or recommendation components are used today to support the often complex product search on the Internet. Faceted filter systems that successively limit the result set according to the set filter settings have proven to be quite successful. However, this method requires clear objectives and domain knowledge on the part of the users. As an alternative, conversational product advisors who select suitable products on the basis of a sequence of questions have gained more importance in recent times, whereby the questions are based more on the tasks and application scenarios of the users than on the technical properties of the products. However, there is currently a lack of approaches that integrate filter systems and conversational advisors in a meaningful and closely coupled way. In this paper an integrated approach is presented, where users can switch between filter systems and advisory dialogues, whereby selection actions in one component have a consistent and transparent effect on the other component and can be further adjusted there. The aim is to better support users with different levels of knowledge of the product type concerned. We describe the requirements for such integrated systems resulting from our approach and report on a user study in which the user behavior and the subjective evaluation were examined in a prototypical implementation.} } @inproceedings{ubo_mods_00136811, author = {Kunkel, Johannes and Donkers, Tim and Michael, Lisa and Barbu, Catalin-Mihai and Ziegler, Jürgen}, title = {Let Me Explain: Impact of Personal and Impersonal Explanations on Trust in Recommender Systems}, booktitle = {Proceedings of the 37th International Conference on Human Factors in Computing Systems (CHI ’19)}, year = {2019}, publisher = {ACM}, address = {New York}, pages = {487:1–487:12}, isbn = {978-1-4503-5970-2}, doi = {10.1145/3290605.3300717}, url = {https://doi.org/10.1145/3290605.3300717}, abstract = {Trust in a Recommender System (RS) is crucial for its overall success. However, it remains underexplored whether users trust personal recommendation sources (i.e. other humans) more than impersonal sources (i.e. conventional RS), and, if they do, whether the perceived quality of explanation provided account for the difference. We conducted an empirical study in which we compared these two sources of recommendations and explanations. Human advisors were asked to explain movies they recommended in short texts while the RS created explanations based on item similarity. Our experiment comprised two rounds of recommending. Over both rounds the quality of explanations provided by users was assessed higher than the quality of the system’s explanations. Moreover, explanation quality significantly influenced perceived recommendation quality as well as trust in the recommendation source. Consequently, we suggest that RS should provide richer explanations in order to increase their perceived recommendation quality and trustworthiness.} } @inproceedings{ubo_mods_00132857, author = {Barbu, Catalin-Mihai and Carbonell, Guillermo and Ziegler, Jürgen}, title = {The Influence of Trust Cues on the Trustworthiness of Online Reviews for Recommendations}, booktitle = {Proceedings of the 34th ACM/SIGAPP Symposium on Applied Computing}, year = {2019}, publisher = {ACM Press}, address = {New York}, pages = {1687–1689}, keywords = {User study}, isbn = {978-1-4503-5933-7}, doi = {10.1145/3297280.3297603}, abstract = {In recent years, recommender systems have started to exploit user-generated content, in particular online reviews, as an additional means of personalizing and explaining their predictions. However, reviews that are poorly written or perceived as fake may have a detrimental effect on the users’ trust in the recommendations. Embedding so-called "trust cues" in the user interface is a technique that can help users judge the trustworthiness of presented information. We report preliminary results from an online user study that investigated the impact of trust cues—in the form of helpfulness votes—on the trustworthiness of online reviews for recommendations.} } @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} } @article{ubo_mods_00127145, author = {Carbonell, Guillermo and Barbu, Catalin-Mihai and Vorgerd, Laura and Brand, Matthias}, title = {The impact of emotionality and trust cues on the perceived trustworthiness of online reviews}, journal = {Cogent Business and Management}, year = {2019}, volume = {6}, number = {1}, pages = {1586062}, keywords = {trust cues}, abstract = {Online reviews and trust cues are two core aspects of e-commerce. Based on these features, users can make informed decisions about the products and services they buy online. Although prior studies have investigated on various review characteristics, the writing style has been examined less frequently. This empirical study simulated an e-commerce platform, in which participants (N =?124) were confronted with the reviews and helpfulness votes of other users while searching for one certain product (i.e. a laptop). The task was to rate how trustworthy or fake the reviews are, and the purchase intention after reading each review. Our results show that a factual writing style is considered more trustworthy, less fake, and entails a higher purchase intention when compared to emotional reviews. The trust cues were only relevant in interaction with variables that measure trust in the Internet as a safe environment for making monetary transactions. Furthermore, we found that trustworthiness influenced purchase intention, but the fakeness perception of the review does not yield such effects. We suggest future studies to understand this result and highlight implications for platform design.}, issn = {2331-1975}, doi = {10.1080/23311975.2019.1586062} } @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_00116566, author = {Loepp, Benedikt and Donkers, Tim and Kleemann, Timm and Ziegler, Jürgen}, title = {Impact of Item Consumption on Assessment of Recommendations in User Studies}, booktitle = {Proceedings of the 12th ACM Conference on Recommender Systems (RecSys ’18)}, year = {2018}, publisher = {ACM}, address = {New York, NY, USA}, pages = {49–53}, keywords = {User Studies}, isbn = {978-1-4503-5901-6}, doi = {10.1145/3240323.3240375}, url = {https://dl.acm.org/doi/10.1145/3240323.3240375?cid=87958660357}, abstract = {In user studies of recommender systems, participants typically cannot consume the recommended items. Still, they are asked to assess recommendation quality and other aspects related to user experience by means of questionnaires. Without having listened to recommended songs or watched suggested movies, however, this might be an error-prone task, possibly limiting validity of results obtained in these studies. In this paper, we investigate the effect of actually consuming the recommended items. We present two user studies conducted in different domains showing that in some cases, differences in the assessment of recommendations and in questionnaire results occur. Apparently, it is not always possible to adequately measure user experience without allowing users to consume items. On the other hand, depending on domain and provided information, participants sometimes seem to approximate the actual value of recommendations reasonably well.} } @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_mods_00090298, author = {Barbu, Catalin-Mihai and Ziegler, Jürgen}, editor = {Neidhardt, Julia and Fesenmaier, Daniel and Kuflik, Tsvi and Wörndl, Wolfgang}, chapter = {}, title = {Co-Staying: a Social Network for Increasing the Trustworthiness of Hotel Recommendations}, series = {CEUR workshop proceedings}, year = {2017}, volume = {1906}, pages = {35–39}, keywords = {Trustworthiness}, abstract = {Recommender systems attempt to match users’ preferences with items. To achieve this, they typically store and process a large amount of user profiles, item attributes, as well as an ever-increasing volume of user-generated feedback about those items. By mining user-generated data, such as reviews, a complex network consisting of users, items, and item properties can be created. Exploiting this network could allow a recommender system to identify, with greater accuracy, items that users are likely to find attractive based on the attributes mentioned in their past reviews as well as in those left by similar users. At the same time, allowing users to visualize and explore the network could lead to novel ways of interacting with recommender systems and might play a role in increasing the trustworthiness of recommendations. We report on a conceptual model for a multimode network for hotel recommendations and discuss potential interactive mechanisms that might be employed for visualizing it.}, url = {http://ceur-ws.org/Vol-1906/paper6.pdf}, booktitle = {RecTour 2017: 2nd Workshop on Recommenders in Tourism : Proceedings of the 2nd Workshop on Recommenders in Tourism co-located with 11th ACM Conference on Recommender Systems (RecSys 2017) Como, Italy, August 27, 2017} } @inproceedings{ubo_mods_00090297, author = {Barbu, Catalin-Mihai and Ziegler, Jürgen}, editor = {Domonkos, Tikk and Pu, Pearl}, chapter = {}, title = {Users’ Choices About Hotel Booking: Cues for Personalizing the Presentation of Recommendations}, series = {CEUR workshop proceedings}, year = {2017}, volume = {1905}, pages = {44–45}, keywords = {Tourism}, abstract = {Personalization in recommender systems has typically been applied to the underlying algorithms. In contrast, the presentation of individual recommendations—specifically, the various ways in which it can be adapted to suit the user’s needs in a more effective manner—has received relatively little attention by comparison. We present the results of an exploratory survey about users’ choices regarding hotel recommendations and draw preliminary conclusions about whether these choices can influence the presentation of recommendations.}, url = {http://ceur-ws.org/Vol-1905/recsys2017_poster22.pdf}, booktitle = {Poster Proceeding of ACM Recsys 2017: Proceedings of the Poster Track of the 11th ACM Conference on Recommender Systems (RecSys 2017) Como, Italy, August 28, 2017} } @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} } @inproceedings{ubo:54813, author = {Gaulke, Werner and Ziegler, Jürgen}, editor = {Ziegler, Jürgen and Nebeling, Michael and Laurence, Nigay}, chapter = {}, title = {Using profiled ontologies to leverage model driven user interface generation}, year = {2015}, publisher = {ACM}, address = {New York, NY, USA}, isbn = {978-1-4503-3646-8}, url = {http://dx.doi.org/10.1145/2774225.2775070}, abstract = {Mobile computing and new input methods have increased the need to create multiple interfaces for one functional core. Automatic generation of user interfaces attempts a solution for this problem. Existing approaches either generate interfaces on the base of a detailed task model or use domain models in conjunction with interface specific annotations and transformation rules. While task models are very time consuming to create and cannot easily be reused domain models lack the flexibility for use cases which are not covered or in conflict with used transformation rules. Based on an overview of existing approaches this paper sets out a conceptual framework which combines both task model and ontology based concepts. It is shown that the proposed combination leads to more abstract and reusable task models.}, booktitle = {Proceedings of the 7th ACM SIGCHI Symposium on Engineering Interactive Computing Systems (EICS ’15)} } @article{ubo:29668, author = {Münter, Daniel and Hussein, Tim}, title = {Adaptive Routenbeschreibungen für Navigationssysteme}, journal = {i-com – Zeitschrift für interaktive und kooperative Medien}, year = {2011}, volume = {10}, number = {1}, pages = {11 –17}, abstract = {In diesem Beitrag stellen wir ein Verfahren zur adaptiven Präsentation für Navigationsgeräte vor, welche auf semantischen Modellen basiert. Dabei reichern wir herkömmliche Routenbeschreibungen mit semantischen Informationen an und präsentieren dem Fahrer lediglich diejenigen Routenanweisungen, an denen er wirklich interessiert ist und blenden überflüssige Anweisungen aus.}, url = {http://duepublico.uni-duisburg-essen.de/servlets/DocumentServlet?id=25471} } @inproceedings{ubo:28374, author = {Münter, Daniel and Hussein, Tim}, chapter = {}, title = {Adaptive presentation of itineraries in navigation systems by means of semantic models}, year = {2011}, abstract = {In this paper, we introduce a technique for adaptive presentation of itineraries in navigation systems based on semantic models. We enrich waypoints with semantic information and display only those waypoints to the driver that he is really interested in, hiding information that will most probably be distracting.}, url = {http://duepublico.uni-duisburg-essen.de/servlets/DocumentServlet?id=24034}, booktitle = {SEMAIS ’11: Proceedings of the 2nd workshop on Semantic Models for Adaptive Interactive Systems (in conjunction with IUI 2011)} } @inproceedings{ubo:26020, author = {Lohmann, Steffen and Tomanek, Katrin and Ziegler, Jürgen and Hahn, Udo}, editor = {Ohlsson, Stellan and Catrambone, Richard}, chapter = {}, title = {Getting at the Cognitive Complexity of Linguistic Metadata Annotation: A Pilot Study Using Eye-Tracking}, year = {2010}, publisher = {Cognitive Science Society}, address = {Austin, TX}, abstract = {We report on an experiment where the decision behavior of annotators issuing linguistic metadata is observed with an eye-tracking device. As experimental conditions we consider the role of textual context and linguistic complexity classes. Still preliminary in nature, our data suggests that semantic complexity is much harder to deal with than syntactic one, and that full-scale textual context is negligible for annotation, with the exception of semantic high-complexity cases. We claim that such observational data might lay the foundation for empirically grounded annotation cost models and the design of cognitively adequate annotation user interfaces.}, url = {http://palm.mindmodeling.org/cogsci2010/papers/0508/paper0508.pdf}, booktitle = {Proceedings of the 32nd Annual Meeting of the Cognitive Science Society (CogSci 2010)} } @inproceedings{ubo:26371, author = {Nacke, E. Lennart and Schild, Jonas and Niesenhaus, Jörg}, editor = {Calvi, Licia and Gualeni, Stefano and Nuijten, Koos and Nacke, E. Lennart and Poels, Karolien}, chapter = {}, title = {Gameplay experience testing with playability and usability surveys – An experimental pilot study}, year = {2010}, publisher = {NHTV Expertise Series}, address = {Breda}, url = {http://www.acagamic.com/uploads/2007/09/Playability-submission.final_.submission.pdf}, abstract = {This pilot study investigates an experimental methodology for gathering data to create correlations between experiential factors measured by a gameplay experience questionnaire and player quality measures, such as playing frequency, choice of game, and playing time. The characteristics of two distinct games were examined concerning the aspects of game experience, subjective game quality, and game usability. Interactions within the three aspects were identified. The results suggest that gameplay experience dimensions flow and immersion are similarly motivating in different game genres, which however might not be equally enjoyable. On the one hand, usability ratings may be positively influenced when a game provides immersion and flow or on the other hand, flow and immersion may be negatively influenced by poor usability ratings. These results emphasize the need for an approach to classify games based on correlation patterns involving game experience, quality, and usability.}, booktitle = {Playability and player experience: Proceedings of the Fun and Games 2010 Workshop} } @inproceedings{ubo:26019, author = {Tomanek, Katrin and Hahn, Udo and Lohmann, Steffen and Ziegler, Jürgen}, editor = {Linguistics, Association for Computational}, chapter = {}, title = {A Cognitive Cost Model of Annotations Based on Eye-Tracking Data}, year = {2010}, publisher = {ACL}, address = {Uppsala}, abstract = {We report on an experiment where the decision behavior of annotators issuing linguistic metadata is observed with an eyetracking device. As experimental conditions we consider the role of textual context and linguistic complexity classes. Still preliminary in nature, our data suggests that semantic complexity is much harder to deal with than syntactic one, and that full-scale textual context is negligible for annotation, with the exception of semantic high-complexity cases. We claim that such observational data might lay the foundation for empirically grounded annotation cost models and the design of cognitively adequate annotation user interfaces.}, isbn = {978-1-932432-66-4}, url = {http://www.aclweb.org/anthology-new/P/P10/P10-1118.pdf}, booktitle = {Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics (ACL 2010)} } @inproceedings{ubo:24767, author = {Hussein, Tim and Münter, Daniel}, chapter = {}, title = {Automated Generation of a Faceted Navigation Interface Using Semantic Models}, year = {2010}, address = {Hong Kong, China}, abstract = {In this paper, we introduce a concept for automated generation of faceted navigation widgets. These widgets are generated on the fly depending on the type of data to be displayed. For this purpose, we use semantic models for data representation and apply generic SPARQL queries, which makes the navigation creation completely independent from the content and structure of the underlying models.}, url = {http://duepublico.uni-duisburg-essen.de/servlets/DocumentServlet?id=21923}, booktitle = {Semantic Models for Adaptive Interactive Systems (SEMAIS), 1st Workshop in conjunction with the International Conference on Intelligent User Interfaces (IUI) 2010} } @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:24670, author = {Nacke, E. Lennart and Drachen, Anders and Kuikkaniemi, Kai and Niesenhaus, Jörg and Korhohnen, J. Hannu and Hoogen, den Wouter van and Ijsselsteijn, Wijnand and Kort, de Yvonne}, editor = {DiGRA}, chapter = {}, title = {Playability and Player Experience Research}, year = {2009}, address = {London, UK}, abstract = {As the game industry matures and games become more and more complex, there is an increasing need to develop scientific methodologies for analyzing and measuring player experience, in order to develop a better understanding of the relationship and interactions between players and games. This panel gathers distinguished European playability and user experience experts to discuss current findings and methodological advancements within player experience and playability research.}, url = {http://www.bth.se/fou/forskinfo.nsf/17e96a0dab8ab6a1c1257457004d59ab/e0a8cdd8cfc0c7e6c125762c005557c0/$file/Nacke-etal-Panel%20Playability%20and%20Player%20Experience.pdf}, booktitle = {Proceedings of DiGRA 2009: Breaking New Ground: Innovation in Games, Play, Practice and Theory.} } @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} } @inproceedings{ubo:14861, author = {Lohmann, Steffen and Kaltz, Wolfgang J. and Ziegler, Jürgen}, editor = {Kühne, Thomas}, chapter = {}, title = {Model-Driven Dynamic Generation of Context-Adaptive Web User Interfaces}, year = {2007}, publisher = {Springer}, address = {Berlin, Heidelberg}, abstract = {The systematic development of user interfaces that enhance interaction quality by adapting to the context of use is a desirable, but also highly challenging task. This paper examines to which extent contextual knowledge can be systematically incorporated in the model-driven dynamic generation of Web user interfaces that provide interaction for operational features. Three parts of the generation process are distinguished: selection, parameterization, and presentation. A semantically enriched service-oriented approach is presented that is based on the Catwalk framework for model interpretation and generation of adaptive, context-aware Web applications. Automation possibilities are addressed and an exemplary case study is presented.}, isbn = {9783540694885}, booktitle = {Models in Software Engineering - Workshops and Symposia at MoDELS 2006} } @inproceedings{ubo:18191, editor = {Lang, Eike and Ziegler, Jürgen and Wissen, Michael and Lang, Eike and Ziegler, Jürgen and Wissen, Michael}, chapter = {}, title = {Modellgetriebene Generierung von Webanwendungsprototypen}, year = {2007}, publisher = {Oldenbourg}, address = {München}, abstract = {Existierende Entwicklungsmethoden und Werkzeuge für das Software-Engineering unterstützen die Entwicklung informationsgetriebener Webanwendungen nur unzureichend und finden in der Praxis daher kaum Anwendung. Im BMBF-geförderten Projekt ?Web Information and Service Engineering“ (WISE) entstand ein werkzeugunterstützter Methodenverbund, der speziell auf die Bedürfnisse bei der Entwicklung webbasierter Informationssysteme zugeschnitten ist. Die Modellierung erfolgt auf Basis von Ontologien und leicht verständlichen Navigationsmodellen. Ein grafischer Editor ermöglicht die Erstellung und Pflege der Modelle und übergibt diese an eine Generatorkomponente, die automatisiert funktionsfähige Webanwendungs-Prototypen erzeugt.}, isbn = {978-3486584967}, url = {http://mc.informatik.uni-hamburg.de/konferenzbaende/mc2007/konferenzband/mc2007_30_lang.pdf}, booktitle = {Mensch und Computer 2007: Interaktion im Plural} } @inproceedings{ubo:14850, author = {Ziegler, Jürgen and Lohmann, Steffen and Kaltz, Wolfgang J.}, editor = {Stary, Christian}, chapter = {}, title = {Kontextmodellierung für adaptive webbasierte Systeme}, year = {2005}, publisher = {Oldenbourg}, address = {München}, abstract = {Adaptive Web-Anwendungen erfordern die Berücksichtigung von Kontext zur Anpassung von Inhalten, Navigationsstrukturen und Präsentationsformen. Für eine systematische Entwicklung kontextadaptiver Systeme sind Methoden der Kontextmodellierung erforderlich, die die komplexen Abhängigkeiten beschreiben. In diesem Beitrag wird ein konzeptioneller Rahmen vorgestellt, der auf einer Taxonomie der verschiedenen Kontextaspekte basiert. Darüber hinaus werden unterschiedliche Mechanismen der Kontextualisierung diskutiert, die von probabilistischen Verfahren bis zu regelbasierten Techniken reichen.}, isbn = {3486578057}, url = {http://mc.informatik.uni-hamburg.de/konferenzbaende/mc2005/konferenzband/muc2005_16_ziegler_etal.pdf}, booktitle = {Mensch Computer 2005: Kunst und Wissenschaft - Grenzüberschreitungen der interaktiven ART} } @inproceedings{ubo:18188, author = {El Jerroudi, Zoulfa and Ziegler, Jürgen and Meissner, Stephan and Philipsenburg, Axel}, editor = {Stary, C.}, chapter = {}, title = {E-Quest: Ein Online-Befragungswerkzeug für Web Usability}, year = {2005}, publisher = {Oldenbourg Verlag}, address = {München}, abstract = {E-Quest ist ein Werkzeug zur automatisierten Online-Befragungen. Es bietet ohne großen Konfigurationsaufwand die Möglichkeit zur komfortablen Gestaltung der Fragebögen und vielfältigen Auswertungsmöglichkeiten, um die Usability einer Webseite zu evaluieren.}, booktitle = {Mensch & Computer 2005: Kunst und Wissenschaft - Grenzüberschreitungen der interaktiven ART} } @article{ubo:14852, author = {Kaltz, Wolfgang J. and Ziegler, Jürgen and Lohmann, Steffen}, title = {Context-aware Web Engineering: Modeling and Applications}, journal = {RIA - Revue d’Intelligence Artificielle, Special Issue on Applying Context-Management}, year = {2005}, volume = {19}, number = {3}, pages = {439–458}, abstract = {This article presents an approach to Web Engineering which aims to account for context-awareness in a comprehensive and integrated fashion, thus enabling an enhanced adaptation of the application to the end-user. A conceptual model, permitting the combination of a domain ontology with context-relevant parameters and a degree of relevance, is presented. Subsequently, the use of such a model in a Web Engineering process is discussed, including appropriate modeling software, and requirements for a runtime system.}, issn = {0992-499X} }