writeup
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@@ -70,15 +70,20 @@ recipes to XML format for input into our application.
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We will gathered data representing several diners' preference for
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approximately 20 meals using a simple survey of the type 'rate on a
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scale of 1 to 10, 10 being favorite and 1 being least favorite'.
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Furthermore we collected data for vegetarians and vegans.
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Furthermore we collected data for vegetarians and allergies.
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%daniel is here
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\paragraph*{Knowledge Engineering}
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We will model each individual user's preferences and needs
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as a Bayesian network, which means a set of independence and
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conditional independence relationships between variables
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\cite{russelnorvig}.
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We model users' preferences using
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a bayes net. In the first layer in Figure \ref{img:bayes_net}
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we capture controll variables like vegan or allergies.
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Those are modeled as boolean variables.
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If the user is allergic or a vegetarian, it will set the variable allergic
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to 0.
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In order to model
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Our model consists of 4 layers,
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each modeling a different aspect of taste and needs.
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In the first layer we capture general meal preferences, like
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