Abstract
Popular online services, such as Amazon.com, provide recommendations for users by using other users’ rating scores for items. In this study, we describe three types of rating systems: score-rated, count-rated, and digital-rated. We hypothesize that digital-rated systems provide the most useful recommendations. Then we analyze the differences in the results of the rating when the granularity of the score changes. Finally, we visualize users by developing a 2-D visualization system that uses a multi-dimensional scaling method.
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© 2007 Springer-Verlag Berlin Heidelberg
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Orimo, E., Koike, H., Masui, T., Takeuchi, A. (2007). Analysis and Evaluation of Recommendation Systems. In: Smith, M.J., Salvendy, G. (eds) Human Interface and the Management of Information. Methods, Techniques and Tools in Information Design. Human Interface 2007. Lecture Notes in Computer Science, vol 4557. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73345-4_18
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DOI: https://doi.org/10.1007/978-3-540-73345-4_18
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-73344-7
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