A High-Speed Heuristic Algorithm for Mining Frequent Patterns in Data Stream

2005 ◽  
Vol 16 (12) ◽  
pp. 2099 ◽  
Author(s):  
Xin ZHANG
Keyword(s):  
Heuristic Algorithm ◽  
Data Stream ◽  
High Speed ◽  
Frequent Patterns

Mining Frequent Patterns over Data Stream under the Time Decaying Model

2010 ◽  
Vol 36 (5) ◽  
pp. 674-684 ◽  
Author(s):  
Feng WU ◽  
Yan ZHONG ◽  
Quan-Yuan WU
Keyword(s):  
Data Stream ◽  
Frequent Patterns

High speed ghost imaging based on a heuristic algorithm and deep learning

2021 ◽  
Author(s):  
Yi-Yi Huang ◽  
Chen Ouyang ◽  
Ke Fang ◽  
Yu-Feng Dong ◽  
Jie Zhang ◽  
...  
Keyword(s):  
Deep Learning ◽  
Heuristic Algorithm ◽  
High Speed ◽  
Ghost Imaging

Research on the Mining Technology of Multimedia Communication Data Flow Based on Computer Network

2013 ◽  
Vol 380-384 ◽  
pp. 3570-3574
Author(s):  
Yong Hong Cheng ◽  
Li Hua Ouyang ◽  
Xin Yan Liu
Keyword(s):  
Data Stream ◽  
High Speed ◽  
Data Flow ◽  
Computer Network ◽  
Multimedia Communication ◽  
Data Stream Mining ◽  
Stream Mining ◽  
Mining Technology ◽  
Daily Work ◽  
Mining Algorithms

computer network multimedia communication has spread all over daily work and life fields, people also have put forward higher requirements for computer multimedia communication network. Based on current network multimedia communication, there are a large amount of data transmission, high-speed and dynamic characteristics, the mining technology of its communication data flow is carried out related to research. In this paper, the frequent item sets of data stream mining technology is carried out related to research, and the classical HCOUNT algorithm is carried out relevant analysis, according to the relevant analysis, the classical HCOUNT algorithm is improved, in order to alleviate possible error problem in data mining. Finally, the data stream mining algorithms are carried out relevant analysis of actual experimental data. Study on the technical aspects of the data flow mining in computer network multimedia communication, it is an important role in the development of the computer network multimedia communication. Study on the improvement of the current algorithm, it provides reference in the similar field of algorithm research

An Efficient Frequent Patterns Mining Algorithm over Data Streams Based on FPD-Graph

2012 ◽  
Vol 433-440 ◽  
pp. 4457-4462 ◽  
Author(s):  
Jun Shan Tan ◽  
Zhu Fang Kuang ◽  
Guo Gui Yang
Keyword(s):  
Data Streams ◽  
Data Stream ◽  
Pattern Mining ◽  
Frequent Pattern Mining ◽  
Frequent Pattern ◽  
Frequent Patterns ◽  
Data Generation ◽  
Experiment Data ◽  
Mining Algorithm ◽  
Head Node

The design of synopses structure is an important issue of frequent patterns mining over data stream. A data stream synopses structure FPD-Graph which is based on directed graph is proposed in this paper. The FPD-Graph contains list head node FPDG-Head and list node FPDG-Node. The operations of FPD-Graph consist of insert operation and deletion operation. A frequent pattern mining algorithm DGFPM based on sliding window over data stream is proposed in this paper. The IBM synthesizes data generation which output customers shopping a data are adopted as experiment data. The DGFPM algorithm not only has high precision for mining frequent patterns, but also has low processing time.

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