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- W1978448228 abstract "Recommender systems are popular tools dealing with the information overload problem in e-commerce web sites. The more they know about the users, the better recommendations they can provide. However, sometimes, in real situations, it is necessary to make guesses about the value of missing but useful data in order to generate a recommendation immediately, rather than waiting the data becomes available. This paper presents an assumption-based multiagent recommender system capable of making these types of assumptions about the preferences of the users. The approach was validate in the tourism domain (recommendation of travel packages). Experiments were conducted to illustrate the impact of various assumption making strategies on the quality of the recommendations as well as the impact of trust assignment." @default.
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- W1978448228 date "2011-11-01" @default.
- W1978448228 modified "2023-09-27" @default.
- W1978448228 title "Improving recommendations through an assumption-based multiagent approach: An application in the tourism domain" @default.
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- W1978448228 doi "https://doi.org/10.1016/j.eswa.2011.05.010" @default.
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