BEGIN:VCALENDAR VERSION:2.0 PRODID:https://github.com/derhansen/sf_event_mgt METHOD:PUBLISH BEGIN:VEVENT UID:2344-4940@fg-abis.gi.de CLASS: PUBLIC SUMMARY:ABIS 2019 DESCRIPTION:ABIS 2019 is an international workshop, organized by the SIG on Adaptivity and User Modeling of the German Gesellschaft für Informatik. Fo r 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 sessi ons, forums, and tutorials. Researchers, Ph.D. students and Web professiona ls obtain and exchange novel ideas, expertise and feedback on ongoing resea rch before submitting their work to major conferences such as CHI, UMAP, WW W and SIGIR.\n\nThis year, we hold the ABIS workshop at ACM Hypertext (Sept ember 17th, 2019 – Hof, Germany).\n\nIntroduction\n\nUser modeling and adap tive systems deal with creating and maintaining a user model with the aim t o adapt interactive systems. User models can be inferred from implicitly ob served user behavior or explicitly entered information, such as the user’s profile data, the user’s current location or items that the user browsed, s earched, tagged or bought earlier.  Applications of personalization include recommendations of items, location-based services, updates on friend activ ities, interest-based portal sites, educative games and personalized guidan ce or help.\n\nWith the ongoing transition from desktop computers to mobile devices and ubiquitous environments, the need for more and better user mod eling and personalization to adapt to changing contexts in various situatio ns is even more important. But this also poses new challenges, including pr ivacy problems and questions of user control. Systems may draw wrong conclu sions about a user’s search actions, limit functionality due to badly desig ned personalized menus, or may inadvertently disclose sensitive information to colleagues and friends.  In addition, the user experience is becoming m ore important in a mobile and connected world. It may not be only important to deliver the absolute best recommendations, but have fast and “good enou gh” recommendations. On the one hand, there is a battle for the attention o f users. On the other hand, the cost of wrong adaptation is very high, user s may quickly switch to different applications and service, if he or she is getting annoyed.\n\nPersonalization does not need to be limited to generat ing lists of recommendations: adaptations such as personalized maps, tailor ed menus, link annotation and scripting potentially have a greater effect o n the user experience. A particular design issue is the explanation of why items are recommended, or which interface elements have been adapted – and how this can be made undone, if needed. And how can one encourage users to inspect and adjust their user profiles, collected information and privacy s ettings?\n\nTopics\n\nTopics include but are not limited to:\n\n Obtaining user data: logging tools, aggregation of data from social networks and oth er Web 2.0 services, location tracking, sensor networks Modeling user data : collaborative filtering, cross-application issues, contextualization and disambiguation, use of ontologies and folksonomies Personalization and rec ommendation: applications in social networks, search, online stores, mobile computing, e-learning, automotive domain, assisting elderly or handicapped persons and other applications areas Privacy issues, transparency, user c ontrol and scrutability Adaptive or intelligent user interfaces: adaptive dialogues, menus or other means of interaction, intelligent agents, feedbac k mechanisms, interaction with ubiquitous environments, new paradigms in hu man-computer interactions Personalized interaction: approaches to personal ize user input or system feedback (involving novel interaction paradigms), related prototypes and studies Adaptive support for learning and teaching: methods and tools for individual support in the knowledge acquisition proc ess, adaptive support for collaborative learning Evaluation and user studi es: laboratory studies, empirical studies in the field and analysis of exis ting corpora of usage data \n\nSubmission\n\nThe ABIS workshop will accept the following submission types:\n\n Full papers (6 pages) representing mat ure work with a proper evaluation Short papers and demos (3 pages) represe nting work in progress and early promising results Vision and position pap ers (2 pages) providing future directions; visions may be bold, but should be backed up with relevant literature Abstract of journal paper or book ch apter (1 page) giving an opportunity to present a published paper or chapte r at this workshop as well \n\nIn addition to regular workshop submissions, we specifically aim to invite Master and Ph.D. students to submit their re search plans and to present their work to the community.\n\n Doctoral cons ortium papers (2-3 pages) present preliminary results or insights, plus con crete open research questions and planned future work Thesis abstracts (1 page) are summaries of recently submitted Bachelor, Master or Ph.D. theses, including a (permanent) link to the paper download \n\nWe are in the proce ss of finalizing our book on Personalized HCI, chapter authors are invited to present their work at the workshop as well.\n\nSubmission Format\n\nPape rs should be formatted according to the ACM Master Article Template format. \n\nSubmission System\n\nSubmissions are accepted via Easychair.\n\nImporta nt Dates\n\n Submissions:  21.06.2019 (Deadline Extension) Notification: 05.07.2019 Camera-Ready: 12.07.2019 Workshop day: 17.09.2019 (Hof, German y) \n\nAccepted Papers\n\nFull Paper:\n\n Unexpected and Unpredictable: Fa ctors That Make Personalized Advertisements Creepy (Eelco Herder, Boping Zh ang)  Descriptive Network Modeling and Analysis for Investigating User Acc eptance in a Learning Management System Context (Parisa Shayan, Roberto Ron dinelli, Menno van Zaanen, Martin Atzmueller) \n\nShort Paper:\n\n Behavio ral Analysis on Socio-Spatial Interaction Networks Concerning User Preferen ces, Interactions and their Perception (Martin Atzmueller, Cicek Güven, Spy roula Masiala, Parisa Shayan, Werner Liebregts) Towards Requirements for I ntelligent Mentoring Systems (Milos Kravcik, Katharina Schmid, Christoph Ig el) Data-Driven Recommendations in a Public Service (Alessandro Piscopo, M aria Panteli, Douglas Penna) Modeling Physiological Conditions for Proacti ve Tourist Recommendations (Rinita Roy, Linus W. Dietz ) \n\nBook Chapter A bstract:\n\n Personalizing the User Interface for People with Disabilities (Julio Abascal, Olatz Arbelaitz, Xabier Gardeazabal, Javier Muguerza, Juan Eduardo Pérez, Ainhoa Yera, Xabier Valencia) Explanations and User Contro l in Recommender Systems (Dietmar Jannach, Michael Jugovac, Ingrid Nunes) Adaptive Workplace Learning Assistance (Milos Kravcik) \n\nTime Schedule\n\ n09:30-11:00\n\n Unexpected and Unpredictable: Factors That Make Personali zed Advertisements Creepy (Eelco Herder, Boping Zhang) [30 min] Behavioral Analysis on Socio-Spatial Interaction Networks Concerning User Preferences , Interactions and their Perception (Martin Atzmueller, Cicek Güven, Spyrou la Masiala, Parisa Shayan, Werner Liebregts) [20 min] Towards Requirements for Intelligent Mentoring Systems (Milos Kravcik, Katharina Schmid, Christ oph Igel) [20 min] Personalizing the User Interface for People with Disabi lities (Julio Abascal, Olatz Arbelaitz, Xabier Gardeazabal, Javier Muguerza , Juan Eduardo Pérez, Ainhoa Yera, Xabier Valencia) [20 min] \n\n11:30-13:0 0\n\n Descriptive Network Modeling and Analysis for Investigating User Acc eptance in a Learning Management System Context (Parisa Shayan, Roberto Ron dinelli, Menno van Zaanen, Martin Atzmueller) [30 min] Data-Driven Recomme ndations in a Public Service (Alessandro Piscopo, Maria Panteli, Douglas Pe nna) [20 min] Modeling Physiological Conditions for Proactive Tourist Reco mmendations (Rinita Roy, Linus W. Dietz ) [20 min] Explanations and User C ontrol in Recommender Systems (Dietmar Jannach, Michael Jugovac, Ingrid Nun es) [20 min] \n\n14:30-16:00\n\n Adaptive Workplace Learning Assistance (M ilos Kravcik) [20 min] Industry Talk: Ricardo Kawase (mobile.de) [30 min] Discussion and Wrapup [40 min] \n\nOrganizers\n\n Mirjam Augstein (Un iversity of Applied Sciences Upper Austria, Hagenberg) Eelco Herder (Radbo ud University) Wolfgang Wörndl (Technical University of Munich) Enes Yigi tbas (Universität Paderborn) \n\nProgram Committee\n\n Maria Bielikova, Sl ovak University of Technology in Bratislava, Slovakia Dominikus Heckmann, Technische Hochschule Amberg-Weiden Dietmar Jannach, University of Klagenf urt Birgitta König-Ries, Friedrich Schiller University of Jena Felicitas Löffler, Friedrich Schiller University of Jena Ernesto William De Luca, Ge org-Eckert-Institut Alexandros Paramythis, Contexity AG Stephan Weibelzah l, Private University of Applied Sciences Göttingen \n\n\n\n LOCATION:Hof University of Applied Sciences DTSTAMP:20260729T140848Z DTSTART:20190917T071500Z DTEND:20190917T150000Z END:VEVENT END:VCALENDAR