[PDF] Top 20 Efficient Mining of Maximal Frequent Itemsets with the Closed and Intersection Approach
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Efficient Mining of Maximal Frequent Itemsets with the Closed and Intersection Approach
... ABSTRACT The application of association rules becomes more and more popular in the field of data ...new approach of mining rules, the Bottom-up Closed ... See full document
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Mining Maximal Frequent Itemsets in Data Streams
... Abstract- Mining streaming data brings not only unique opportunities but also new difficult challenges of online algorithm design, such as one streaming data scan, bounded memory requirement, fast ... See full document
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Online Mining (Recently) Maximal Frequent Itemsets over Data Streams
... mines the set of all maximal frequent itemsets over the entire history of the streaming ...In the DSM-MFI algorithm, a new in- memory summary data structure ... See full document
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DSM-FI: An efficient algorithm for mining frequent itemsets in data streams
... In the BTS algorithm, two estimated parameters: minimum support threshold s, and maxi- mum support error threshold ε, are used, where 0 < ε ≤ s < ...1. The incoming data stream is conceptually ... See full document
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DSM-FI: an efficient algorithm for mining frequent itemsets in data streams
... In the BTS algorithm, two estimated parameters: minimum support threshold s, and maxi- mum support error threshold ε, are used, where 0 < ε ≤ s < ...1. The incoming data stream is conceptually ... See full document
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Mining Frequent Itemsets from Data Streams with a Time-Sensitive Sliding Window
... address the issue of the limited memory space. Among the data structures maintained for mining and discounting in our approach, DT often consumes most of the ... See full document
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Incremental mining of closed inter-transaction itemsets over data stream sliding windows
... tree-based approach, ICMiner, to discover closed inter-transaction itemsets ...generation and repeated support counting. Dong et al. proposed a novel approach to mine the ... See full document
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Mining frequent patterns with item, aggregation, and cardinality constraints
... deal with multiple types of ...types of constraints are considered, including item constraint, aggregation constraint, and cardinality ...an efficient algorithm, MCFP (Multi-Constrained ... See full document
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Mining top-k frequent patterns in the presence of the memory constraint
... paper efficient solu- tions, called MTK (standing for the Memory-constraint top-k frequent-pattern mining) and MTK_Close, to discover pure top-k frequent patterns and ... See full document
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Efficient mining of generalized association rules with non-uniform minimum support
... Our approach is that, in each pass k, rather than counting all candidates in C k as in MMS_Cumulate, we count the supports for candidates in TC k ...along with their descendants in RC k ...over ... See full document
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Efficient Maintenance and Mining of Frequent Itemsets over Online Data Streams with a Sliding Window
... is with the Department of Computer Science, National Chiao-Tung University, Hsinchu, Taiwan 300, ...in the stream should be processed as fast as possible. Fourth, the analytical outputs ... See full document
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An Efficient Algorithm for Mining Frequent Itemsets over the Entire History of Data Streams
... record and click streams in Web applications, performance measurement in network monitoring and traffic management, call records in telecommunications, ...etc. Mining such streaming data differs from ... See full document
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Mining frequent itemsets over data streams using efficient window sliding techniques
... Online mining of frequent itemsets over a stream sliding window is one of the most important problems in stream data mining with broad ...since the streaming ... See full document
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Incremental updates of closed frequent itemsets over continuous data streams
... to the stream processing model (Zhu & Shasha, 2002), the research of mining frequent patterns over data streams can be divided into three categories: landmark win- dows (Jin and ... See full document
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Mining fuzzy frequent itemsets for hierarchical document clustering
... Conclusions and future directions Although numerous interesting document clustering methods have been extensively studied for many years, the high computation complexity and space need still make ... See full document
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Mining Frequent Itemsets for data streams over Weighted Sliding Windows
... propose the framework of the weighted sliding windows for data stream ...on the model, users can specify the number of windows, the size of a window, and ... See full document
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Efficient mining of temporal emerging itemsets from data streams
... for mining temporal emerging frequent itemsets from data streams effi- ciently and ...effectively. The temporal emerging frequent itemsets are those that are infrequent in ... See full document
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Online Mining Maximal Frequent Structures in Continuous Landmark Melody Streams
... data and experiment set-up To evaluate the performance of MMS LMS algo- rithm, two experiments are ...performed. The exper- iments were carried out on the IBM synthetic market-basket ... See full document
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Online mining maximal frequent structures in continuous landmark melody streams
... data and experiment set-up To evaluate the performance of MMS LMS algo- rithm, two experiments are ...performed. The exper- iments were carried out on the IBM synthetic market-basket ... See full document
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Fast and memory efficient mining of high-utility itemsets from data streams: with and without negative item profits
... applications of mining high-utility itemsets are changed from mining traditional data sets to mining transactional data streams in recent ...proposed the first method, called ... See full document
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