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Utility-pattern mining in data has received a lot of attention from the knowledge discovery in database (KDD) community due to its high potential for many applications such as finance, biomedicine, manufacturing, e-commerce, and social media. Current research in utility-pattern mining primarily focuses on discovering patterns of high value (e.g., high profit) in large databases and analyzing/learning important factors (e.g., economic factors) in a data mining process. One of the most popular applications of utility mining is the analysis of large transactional databases to discover high-utility itemsets, which are sets of items that yield a high profit when purchased together.