document: Mining preferences from superior and inferior examples Mining user preferences plays a critical role in many important applications such as customer relationship management ( CRM ) , product and service recommendation , and marketing campaigns . In this paper , we identify an interesting and practical problem of mining user preferences : in a multidimensional space where the user preferences on some categorical attributes are unknown , from some superior and inferior examples provided by a user , can we learn about the user 's preferences on those categorical attributes ? We model the problem systematically and show that mining user preferences from superior and inferior examples is challenging . Although the problem has great potential in practice , to the best of our knowledge , it has not been explored systematically before . As the first attempt to tackle the problem , we propose a greedy method and show that our method is practical using real data sets and synthetic data sets .
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