@inproceedings{kleemann2023,
  abstract = {Today’s e-commerce websites often provide many different components, such as filters and conversational product advisors, to help users find relevant items. However, filters and advisors are often presented separately and treated as independent entities so that the previous input is discarded when users switch between them. This leads to memory loads and disruptions during the search process. In addition, the reasoning behind the advisors’ results is often not transparent. To overcome these limitations, we propose a novel approach that exploits a graph structure to create an integrated system that allows a seamless coupling between filters and advisors. The integrated system utilizes the graph to suggest appropriate filter values and items based on the user’s answers in the advisor. Moreover, it determines follow-up questions based on the filter values set by the user. The interface visualizes and explains the relationship between a given answer and its relevant features to achieve increased transparency in the guidance process. We report the results of an empirical user study with 120 participants that compares the integrated system to a system in which the filtering and advisory mechanisms operate separately. The findings indicate that displaying recommendations and explanations directly in the filter component can increase acceptance and trust in the system. Similarly, combining the advisor with the filters along with the displayed explanations leads to significantly higher levels of knowledge about the relevant product features.},
  address = {Cham},
  author = {Kleemann, Timm and Ziegler, Jürgen},
  series = {Lecture Notes in Computer Science},
  booktitle = {Human-Computer Interaction – INTERACT 2023 : 19th IFIP TC13 International Conference, York, UK, August 28 – September 1, 2023, Proceedings, Part III},
  editor = {Abdelnour Nocera, José and Kristı́n Lárusdóttir, Marta and Petrie, Helen and Piccinno, Antonio and Winckler, Marco},
  isbn = {9783031422850},
  issn = {0302-9743},
  volume = {14144},
  doi = {10.1007/978-3-031-42286-7_8},
  pages = {137–159},
  publisher = {Springer Nature Switzerland},
  title = {Blending Conversational Product Advisors and Faceted Filtering in a Graph-Based Approach},
  url = {https://doi.org/10.1007/978-3-031-42286-7_8},
  note = {10.1007/978-3-031-42286-7_8},
  language = {en},
  keywords = {Search interfaces; explanations; knowledge graph},
  year = {2023},
  month = {aug},
  day = {25},
  month_numeric = {8}
}


@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}
}