ABIS 2019 - 23rd Intl. Workshop on Personalization and Recommendation on the Web and Beyond
ABIS 2019 is an international workshop, organized by the SIG on Adaptivity and User Modeling of the German Gesellschaft fur Informatik. For more than 20 years, the ABIS Workshop has been a highly interactive forum for discussing the state of the art in personalization and user modeling. Latest developments in industry and research are presented in plenary sessions, forums, and tutorials.
For the first time, ABIS will be hosted by the ACM International Conference on Hypertext and Social Media (HT'19), which will celebrate its 30th anniversary this year. ABIS 2019 additionally features the introduction of the new book on Personalized Human-Computer Interaction, edited by the workshop chairs and to be published in 2019 by DeGruyter.
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- KonferenzbeitragAdaptive Workplace Learning Assistance(Proceedings of the 23rd International Workshop on Personalization and Recommendation on the Web and Beyond, 2019) Kravčík, MilošWorkplace learning has been a part of our lives for a long time already. However, new technological opportunities can radically change not only formal, but also informal (unintentional) learning, which is typical for the workplace. Nowadays companies face a new challenge: the transition towards Industry 4.0. In this regard, information technology should support the whole spectrum of educational methodologies, including personalized guidance, collaborative learning, training of practical skills, as well as meta-cognitive scaffolding.
- KonferenzbeitragBehavioral Analysis on Socio-Spatial Interaction Networks concerning User Preferences, Interactions and their Perception(Proceedings of the 23rd International Workshop on Personalization and Recommendation on the Web and Beyond, 2019) Atzmueller, Martin; Güven, Cicek; Masiala, Spyroula; Mackenbach, Rick; Shayan, Parisa; Liebregts, WernerThis paper investigates socio-spatial interaction networks for user modeling: We analyze preferences and perceptions of socio-proximity human interactions in relation to the observed interactions. The analysis is performed on a real-world dataset capturing interaction networks using wearable sensors coupled with self-report questionnaires about preferences and perception of those interactions.
- KonferenzbeitragDescriptive Network Modeling and Analysis for Investigating User Acceptance in a Learning Management System Context(Proceedings of the 23rd International Workshop on Personalization and Recommendation on the Web and Beyond, 2019) Shayan, Parisa; Rondinelli, Roberto; van Zaanen, Menno; Atzmueller, MartinLearning Management Systems (LMSs) play a significant role in educational technology. In this paper, we analyze different approaches in order to investigate the acceptance of an LMS. Utilizing questionnaire information structured on the Technology Acceptance Model (TAM), we apply descriptive network modeling and analysis complementing basic statistical analysis in order to identify specific patterns in the user data. We present the applied analysis methodology in detail, and demonstrate the connection to user modeling:here, descriptive statistics indicate student satisfaction with the usage (acceptance level) as a whole; network analysis indicates the level of variability w.r.t. the user questions, while specific patterns or motifs show the satisfaction levels for the different networks.
- KonferenzbeitragExplanations and User Control in Recommender Systems(Proceedings of the 23rd International Workshop on Personalization and Recommendation on the Web and Beyond, 2019) Jannach, Dietmar; Jugovac, Michael; Nunes, Ingrid
- KonferenzbeitragModeling Physiological Conditions for Proactive Tourist Recommendations(Proceedings of the 23rd International Workshop on Personalization and Recommendation on the Web and Beyond, 2019) Roy, Rinita; Dietz, Linus W.Mobile proactive tourist recommender systems can support tourists by recommending the best choice depending on different contexts related to themselves and the environment. In this paper, we propose to utilize wearable sensors to gather health information about a tourist and use them for recommending activities. We discuss a range of wearable devices, sensors to infer physiological conditions of the users, and exemplify the feasibility using a popular self-quantification mobile app. Our main contribution is a data model to derive relations between the parameters measured by the wearable sensors, such as heart rate, body temperature, blood pressure, and use them to infer the physiological condition of a user. This model can then be used to derive classes of tourist activities that determine which items should be recommended.
- KonferenzbeitragPersonalizing the User Interface for People with Disabilities(Proceedings of the 23rd International Workshop on Personalization and Recommendation on the Web and Beyond, 2019) Abascal, Julio; Gardeazabal, Xabier; Pérez, Juan Eduardo; Valencia, Xabier; Arbelaitz, Olatz; Muguerza, Javier; Yera, AinhoaComputer applications provide people with disabilities with unique opportunities for interpersonal communication, social interaction and active participation. However, rigid user interfaces often present accessibility barriers to people with physical, sensory or cognitive impairments. User interface personalization is crucial to overcome these barriers, enabling computer access to a considerable section of the population with disabilities. Adapting the user interface to people with disabilities requires taking into consideration their physical, sensory or cognitive abilities and restrictions and hence providing alternative access procedures according to their capacities. In the chapter 15, "Personalizing the User Interface for People with Disabilities" [1], we present methods and techniques that are being applied to research and practice on user interface personalization for people with disabilities. In addition, we discuss possible approaches for diverse application fields where personalization is required: accessibility to the web using transcoding, web mining for eGovernment, and human-robot interaction for people with severe motor restrictions.
- KonferenzbeitragTowards Requirements for Intelligent Mentoring Systems(Proceedings of the 23rd International Workshop on Personalization and Recommendation on the Web and Beyond, 2019) Kravčík, Milos; Schmid, Katharina; Igel, ChristophThe raising demands on qualification increase the importance of technology as a facilitator in the educational process on the side of both receivers and providers. Beside the cognitive aspects, also metacognitive, emotional and motivational ones play a crucial role in learning. A challenge is to recognize the affective status of participants and react to them accordingly, in order to make the learning experience effective and efficient. Various approaches were investigated and reported in the literature. In order to develop mentoring support at the university level in concrete settings, we researched them and tried to identify the key requirements for our solution. Based on these requirements, we plan to design intelligent knowledge services for scalable mentoring processes.
- KonferenzbeitragUnexpected and Unpredictable: Factors That Make Personalized Advertisements Creepy(Proceedings of the 23rd International Workshop on Personalization and Recommendation on the Web and Beyond, 2019) Herder, Eelco; Zhang, BopingPersonalized advertisements are the price we have to pay for free social media platforms. Various studies have been carried out on user acceptance of such advertisements in general and most countries have adopted laws and regulations with respect to privacy and data protection. However, not all advertisements evoke the same responses: some ads are considered more annoying, intrusive or creepy than others. In this paper, we present the results of an observational study on user responses to actual Facebook advertisements. The results show that mismatches in terms of context, unexpected data collection or inference, overly generic explanations and repetition are common causes of anxiety and distrust.