We describe Order-Based Retrieval, which is an approach to case retrieval based on the application of partial orders to the case base. We argue that it is well-suited to product recommender applications because, as well as retrieving products that best match customer-specified 'ideal' attribute-values, it also: allows the customer to specify soft constraints; gives a natural semantics and implementation to tweaks; and delivers an inherently diverse result set.
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