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- W1572319277 abstract "The evolution of information technologies is consolidating recommender systems as essential tools in e-commerce. To date, these systems have focused on discovering the items that best match the preferences, interests and needs of individual users, to end up listing those items by decreasing relevance in some menus. In this paper, we propose extending the current scope of recommender systems to better support trading activities, by automatically generating interactive applications that provide the users with personalized commercial functionalities related to the selected items. We explore this idea in the context of Digital TV advertising, with a system that brings together semantic reasoning techniques and new architectural solutions for web services and mashups." @default.
- W1572319277 created "2016-06-24" @default.
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- W1572319277 date "2009-01-01" @default.
- W1572319277 modified "2023-10-16" @default.
- W1572319277 title "Automatic Generation of Mashups for Personalized Commerce in Digital TV by Semantic Reasoning" @default.
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- W1572319277 doi "https://doi.org/10.1007/978-3-642-03964-5_13" @default.
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