Search (2 results, page 1 of 1)

  • × author_ss:"Schraefel, M.C."
  • × theme_ss:"Suchoberflächen"
  1. Wilson, M.L.; Schraefel, M.C.; White, R.W.: Evaluating advanced search interfaces using established information-seeking models (2009) 0.00 
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    Abstract
    When users have poorly defined or complex goals, search interfaces that offer only keyword-searching facilities provide inadequate support to help them reach their information-seeking objectives. The emergence of interfaces with more advanced capabilities, such as faceted browsing and result clustering, can go some way toward addressing such problems. The evaluation of these interfaces, however, is challenging because they generally offer diverse and versatile search environments that introduce overwhelming amounts of independent variables to user studies; choosing the interface object as the only independent variable in a study would reveal very little about why one design outperforms another. Nonetheless, if we could effectively compare these interfaces, then we would have a way to determine which was best for a given scenario and begin to learn why. In this article, we present a formative inspection framework for the evaluation of advanced search interfaces through the quantification of the strengths and weaknesses of the interfaces in supporting user tactics and varying user conditions. This framework combines established models of users and their needs and behaviors to achieve this. The framework is applied to evaluate three search interfaces and demonstrates the potential value of this approach to interactive information retrieval evaluation.
    Type
    a
  2. Tsandilas, T.; Schraefel, M.C.: Usable adaptive hypermedia systems (2004) 0.00 
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    Abstract
    Adaptive interfaces have received much criticism because adaptation and automatic assistance generally contradict the principles of direct-manipulation interfaces. In addition, their success depends highly on the ability of user models to capture the goals and needs of the users. As the construction of user models is often based on poor evidence, even the most advanced learning algorithms may fail to infer accurately the user goals. Previous research has put little emphasis on investigating usability problems of adaptive systems and developing interaction techniques that could resolve these problems. This paper examines these problems and presents an interaction model for adaptive hypermedia (AH) that merges adaptive support and direct manipulation. This approach is built upon a new content adaptation technique that derives from fisheye views. This adaptation technique supports incremental and continuous adjustments of the adaptive views of hypermedia documents and balances between focus and context. By combining this technique with visual representations and controllers of user models, we form a twofold interaction model that enables users to move quickly between adaptation and direct control. Two preliminary user studies exhibit the strengths of our proposed interaction model and adaptation technique. Future extensions to our work are outlined based on the weaknesses and limitations that the studies revealed.
    Type
    a

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