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Auflistung nach Schlagwort "explanations"

1 - 3 von 3
  • Workshopbeitrag
    Argumentative explanations for recommendations - Effect of display style and profile transparency
    (Mensch und Computer 2020 - Workshopband, 2020) Hernandez-Bocanegra, Diana Carolina; Ziegler, Jürgen
    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.
  • Zeitschriftenartikel
    Explaining Review-Based Recommendations: Effects of Profile Transparency, Presentation Style and User Characteristics
    (i-com: Vol. 19, No. 3, 2021) Hernandez-Bocanegra, Diana C.; Ziegler, Jürgen
    Providing explanations based on user reviews in recommender systems (RS) may increase users’ perception of transparency or effectiveness. However, little is known about how these explanations should be presented to users, or which types of user interface components should be included in explanations, in order to increase both their comprehensibility and acceptance. To investigate such matters, we conducted two experiments and evaluated the differences in users’ perception when providing information about their own profiles, in addition to a summarized view on the opinions of other customers about the recommended hotel. Additionally, we also aimed to test the effect of different display styles (bar chart and table) on the perception of review-based explanations for recommended hotels, as well as how useful users find different explanatory interface components. Our results suggest that the perception of an RS and its explanations given profile transparency and different presentation styles, may vary depending on individual differences on user characteristics, such as decision-making styles, social awareness, or visualization familiarity.
  • Konferenzbeitrag
    What Does My Classifier Learn? A Visual Approach to Understanding Natural Language Text Classifiers
    (Software Engineering und Software Management 2018, 2018) Winkler, Jonas Paul; Vogelsang, Andreas
    Neural Networks have been utilized to solve various tasks such as image recognition, text classification, and machine translation and have achieved exceptional results in many of these tasks. However, understanding the inner workings of neural networks and explaining why a certain output is produced are no trivial tasks. Especially when dealing with text classification problems, an approach to explain network decisions may greatly increase the acceptance of neural network supported tools. In this paper, we present an approach to visualize reasons why a classification outcome is produced by convolutional neural networks by tracing back decisions made by the network. The approach is applied to various text classification problems, including our own requirements engineering related classification problem. We argue that by providing these explanations in neural network supported tools, users will use such tools with more confidence and also may allow the tool to do certain tasks automatically.