论文信息 - Uncertain Data Flow Mining Algorithm Based on Hybrid Model

Uncertain Data Flow Mining Algorithm Based on Hybrid Model

Sliding window technique in data mining algorithm is one of the most widely used technology, considering the characteristics of uncertain data stream and SRUF-mine algorithm in the profile structure tree storage potential, the expectations of frequent itemsets will appear deviation, on the basis of the joined the error factor to improve the accuracy.In SRUF-mine algorithm on the basis of the combination of data stream processing technology, is proposed based on hybrid model of uncertain data flow algorithm for mining frequent itemsets – DSUFIM-mine is presented. Experiments show that DSUFIM-mine algorithm has high accuracy and practical significance.

Ru Li | Junrui Yang | Cai Yang

[1] Keun Ho Ryu,et al. Sliding window based weighted maximal frequent pattern mining over data streams , 2014, Expert Syst. Appl..

[2] Carson Kai-Sang Leung,et al. Frequent itemset mining of uncertain data streams using the damped window model , 2011, SAC.

[3] Ning Zhang,et al. Efficient frequent itemset mining methods over time-sensitive streams , 2014, Knowl. Based Syst..

[4] Carson Kai-Sang Leung,et al. A Tree-Based Approach for Frequent Pattern Mining from Uncertain Data , 2008, PAKDD.

[5] Abdelkader Hameurlain,et al. Transactions on Large-Scale Data- and Knowledge-Centered Systems VIII , 2013, Lecture Notes in Computer Science.

[6] Wan Changxuan,et al. Frequent Patterns Mining over Uncertain Data Streams Based on Probability Decay Window Model , 2012 .

[7] Yuni Xia,et al. Hyper-structure mining of frequent patterns in uncertain data streams , 2012, Knowledge and Information Systems.

[8] Carson Kai-Sang Leung,et al. Mining of Frequent Itemsets from Streams of Uncertain Data , 2009, 2009 IEEE 25th International Conference on Data Engineering.