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Itemset mining has been an active area of research due to its successful application in various data mining scenarios including finding association rules. Though most of the past work has been on finding frequent itemsets, infrequent itemset mining has demonstrated its utility in web mining, bioinformatics and other fields. In this paper, we propose a new(More)
We focus on crowd-powered ltering, i.e., ltering a large set of items using humans. Filtering is one of the most commonly used building blocks in crowdsourcing applications and systems. While solutions for crowd-powered ltering exist, they make a range of implicit assumptions and restrictions, ultimately rendering them not powerful enough for real-world(More)
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