Learning Label Trees for Probabilistic Modelling of Implicit Feedback
نویسندگان
چکیده
Collaborative filtering is the method of choice for inferring complex user preference patterns from large collections of feedback data. •Explicit feedback: ratings given by users to items – Received a lot of attention: several very effective methods – Ratings can be scarce or expensive to collect • Implicit feedback: user purchase or click history – Easier to collect than explicit feedback: produced by common user actions – The existing methods are not fully probabilistic
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Learning Item Trees for Probabilistic Modelling of Implicit Feedback
User preferences for items can be inferred from either explicit feedback, such as item ratings, or implicit feedback, such as rental histories. Research in collaborative filtering has concentrated on explicit feedback, resulting in the development of accurate and scalable models. However, since explicit feedback is often difficult to collect it is important to develop effective models that take...
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