Abstract
We propose a visual exploration technique, “visual exploration by example,” for recommendations in a social filtering system. A dynamic semantic map of items, rearranged dynamically for each query or filtering result, gives explanations of the result with contextual information and helps the user’s composition of a new query. We also have introduced visual interaction techniques to the map to examine more detailed relationship of filtering results: coloring by rating and highlighting by similarity. We demonstrate an example of the user’s exploration using a prototype interface for a movie database.
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Tatemura, J. (2000). Visual Exploration for Social Recommendations. In: Arisawa, H., Catarci, T. (eds) Advances in Visual Information Management. VDB 2000. IFIP — The International Federation for Information Processing, vol 40. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-35504-7_5
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DOI: https://doi.org/10.1007/978-0-387-35504-7_5
Publisher Name: Springer, Boston, MA
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