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[PDF] Top 20 An Efficient Method for Mining Temporal Emerging Itemsets in Data Streams

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An Efficient Method for Mining Temporal Emerging Itemsets in Data Streams

An Efficient Method for Mining Temporal Emerging Itemsets in Data Streams

... Apriori In this experiment, we compare the average execution time in different support values between Apriori and ...frequent itemsets. However, Apriori can only find frequent itemsets, while ... See full document

6

Efficient mining of temporal emerging itemsets from data streams

Efficient mining of temporal emerging itemsets from data streams

... Abstract In this paper, we propose a new method, namely EFI-Mine, for mining temporal emerging frequent itemsets from data streams effi- ciently and ...The ... See full document

9

An efficient algorithm for mining temporal high utility itemsets from data streams

An efficient algorithm for mining temporal high utility itemsets from data streams

... shown in Table 3, D  indicates the unchanged por- tion of an ongoing transaction ...of an ongoing transaction database are denoted by D  and D + , ...maintain temporal high utility ... See full document

13

DSM-FI: An efficient algorithm for mining frequent itemsets in data streams

DSM-FI: An efficient algorithm for mining frequent itemsets in data streams

... streaming data makes it essential to use the online algorithms which require only one scan over the data streams for knowledge ...the data into the main memory or even in ... See full document

19

DSM-FI: an efficient algorithm for mining frequent itemsets in data streams

DSM-FI: an efficient algorithm for mining frequent itemsets in data streams

... streaming data makes it essential to use the online algorithms which require only one scan over the data streams for knowledge ...the data into the main memory or even in ... See full document

19

An Efficient Algorithm for Mining Frequent Itemsets over the Entire History of Data Streams

An Efficient Algorithm for Mining Frequent Itemsets over the Entire History of Data Streams

... click streams in Web applications, performance measurement in network monitoring and traffic management, call records in telecommunications, ...etc. Mining such streaming data ... See full document

10

Mining Maximal Frequent Itemsets in Data Streams

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

6

Mining frequent itemsets over data streams using efficient window sliding techniques

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 ...streaming data possess some challenging ... See full document

12

Mining Frequent Itemsets for data streams over Weighted Sliding Windows

Mining Frequent Itemsets for data streams over Weighted Sliding Windows

... Conclusions In this paper, we propose the framework of the weighted sliding windows for data stream ...weight for each window. Thus, a more significant data section can be assigned a ... See full document

6

Efficient Maintenance and Mining of Frequent Itemsets over Online Data Streams with a Sliding Window

Efficient Maintenance and Mining of Frequent Itemsets over Online Data Streams with a Sliding Window

... sylee@csie.nctu.edu.tw). in the stream should be processed as fast as ...streaming data makes it essential to use the algorithms which require only one scan over the stream for knowledge ...the ... See full document

6

Online Mining (Recently) Maximal Frequent Itemsets over Data Streams

Online Mining (Recently) Maximal Frequent Itemsets over Data Streams

... Conclusions In this paper, we proposed a new, single-pass algorithm called DSM-MFI which mines the set of all maximal frequent itemsets over the entire history of the streaming ...data. In the ... See full document

8

An efficient algorithm for mining high utility itemsets with negative item values in large databases

An efficient algorithm for mining high utility itemsets with negative item values in large databases

... Utility itemsets typically consist of items with different values such as utilities, and the aim of utility mining is to identify the itemsets with highest ...utilities. In the past studies on ... See full document

12

Fast and memory efficient mining of high-utility itemsets from data streams: with and without negative item profits

Fast and memory efficient mining of high-utility itemsets from data streams: with and without negative item profits

... of mining high-utility itemsets are changed from mining traditional data sets to mining transactional data streams in recent ...first method, called ... See full document

28

Mining Frequent Itemsets from Data Streams with a Time-Sensitive Sliding Window

Mining Frequent Itemsets from Data Streams with a Time-Sensitive Sliding Window

... Table In this section, we refine DT_maintenance to address the issue of the limited memory ...the data structures maintained for mining and discounting in our approach, DT often ... See full document

12

Progressive Partition Miner: An Efficient Algorithm for Mining General Temporal Association Rules

Progressive Partition Miner: An Efficient Algorithm for Mining General Temporal Association Rules

... Workload For obtaining reliable experimental results, the method to generate synthetic transactions we employed in this study is similar to the ones used in prior works [4], ...frequent ... See full document

14

Adherence clustering: an efficient method for mining market-basket clusters

Adherence clustering: an efficient method for mining market-basket clusters

... of data characteristics. These transactions mimic the transactions in the real world retailing ...itemset. An example of such a set might be sheets, pillow case, comforter, and ... See full document

17

Mining spatio-temporal information on microblogging streams using a density-based online clustering method

Mining spatio-temporal information on microblogging streams using a density-based online clustering method

... information for many fields of ...text streams for a while, and even some popular microblogging services such as Twitter did provide information of top trending topics for selection, it is ... See full document

9

Sliding window filtering: an efficient method for incremental mining on a time-variant database

Sliding window filtering: an efficient method for incremental mining on a time-variant database

... workload For obtaining reliable experimental results, the method to generate synthetic transactions we employed in this study is similar to the ones used in prior works ...frequent ... See full document

18

Energy efficient strategies for object tracking in sensor networks: A data mining approach

Energy efficient strategies for object tracking in sensor networks: A data mining approach

... objects’ temporal movement patterns in OTSNs so as to enhance the energy ...efficiency. In this paper, we propose a novel data mining method named TMP-Mine with a special ... See full document

10

An Improved Data Mining Approach Using Predictive Itemsets

An Improved Data Mining Approach Using Predictive Itemsets

... algorithms for mining association rules from transactions are proposed, most of which are executed in level-wise ...is, itemsets containing single items are processed first, then ... See full document

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