Frequent Itemsets Mining with Differential Privacy Over Large-Scale Data
نویسندگان
چکیده
منابع مشابه
Mining Frequent Itemsets Over Arbitrary Time Intervals in Data Streams
Mining frequent itemsets over a stream of transactions presents di cult new challenges over traditional mining in static transaction databases. Stream transactions can only be looked at once and streams have a much richer frequent itemset structure due to their inherent temporal nature. We examine a novel data structure, an FP-stream, for maintaining information about itemset frequency historie...
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This paper considers the problem of mining recent frequent itemsets over data streams. As the data grows without limit at a rapid rate, it is hard to track the new changes of frequent itemsets over data streams. We propose an efficient one-pass algorithm in sliding windows over data streams with an error bound guarantee. This algorithm does not need to refer to obsolete transactions when 316 C....
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In this paper, we propose a new framework for data stream mining, called the weighted sliding window model. The proposed model allows the user to specify the number of windows for mining, the size of a window, and the weight for each window. Thus, users can specify a higher weight to a more significant data section, which will make the mining result closer to user’s requirements. Based on the w...
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In recent years, due to the wide applications of uncertain data, mining frequent itemsets over uncertain databases has attracted much attention. In uncertain databases, the support of an itemset is a random variable instead of a fixed occurrence counting of this itemset. Thus, unlike the corresponding problem in deterministic databases where the frequent itemset has a unique definition, the fre...
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Association Rules are the most important tool to discover the relationships among the attributes in a database. The existing Association Rule mining algorithms are applied on binary attributes or discrete attributes, in case of discrete attributes there is a loss of information and these algorithms take too much computer time to compute all the frequent itemsets. By using Genetic Algorithm (GA)...
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ژورنال
عنوان ژورنال: Journal of Advanced Research in Dynamical and Control Systems
سال: 2019
ISSN: 1943-023X
DOI: 10.5373/jardcs/v11sp11/20193033