Abstract
Computerized presentation slides have become essential for effective business meetings, classroom discussions, and even general events and occasions. With the exploding number of online resources and materials, locating the slides of high quality is a daunting challenge. In this study, we present a new, comprehensive framework of information quality developed specifically for computerized presentation slides on the basis of a user study involving 60 university students from two universities and extensive coding analysis, and explore the possibility of automatically detecting the information quality of slides. Using the classifications made by human annotators as the golden standard, we compare and evaluate the performance of alternative information quality features and dimensions. The experimental results support the validity of the proposed approach in automatically assessing and classifying the information quality of slides.
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Kim, S., Jung, W., Han, K., Lee, JG., Yi, M.Y. (2014). Quality-Based Automatic Classification for Presentation Slides. In: de Rijke, M., et al. Advances in Information Retrieval. ECIR 2014. Lecture Notes in Computer Science, vol 8416. Springer, Cham. https://doi.org/10.1007/978-3-319-06028-6_69
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DOI: https://doi.org/10.1007/978-3-319-06028-6_69
Publisher Name: Springer, Cham
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