DocumentCode
506913
Title
Rule-Chain Incremental Mining Algorithm Based on Directed Graph
Author
Ning, Hongyun ; Zhang, Zhiying ; Zhang, Degan
Author_Institution
Tianjin Key Lab. of Intell. Comput. & Novel Software Technol., Tianjin Univ. of Technol., Tianjin, China
Volume
2
fYear
2009
fDate
14-16 Aug. 2009
Firstpage
118
Lastpage
122
Abstract
Aiming to discover the rule-chains directly, a novel graph-based online incremental mining algorithm (RIOMining) is proposed. Firstly, an interrelated bitmap based on a directed graph (PAGraph) is designed to compress the rule-chain information for storage. The compressed storage of the directed-graph effectively avoids repetitious database scanning and makes meaningful rules found more conveniently. Secondly, four theorems about discovery and pruning of frequent path in the graph are proved, so as to the rule-chains could be iteratively generated by searching incremental paths, while the theorems narrow the search scope and promote the performance by properly pruning and extending paths. It effectively reduces the redundancy calculation. Comparing it with other two fast mining algorithms, DLG and FP-growth, experimental result shows that it can mine rule-chains of high quality, especially, it is of real-time accuracy, and thereby it can be widely applied to dynamic network environment.
Keywords
data mining; directed graphs; DLG-growth; FP-growth; directed graph; interrelated bitmap; rule-chain incremental mining algorithm; rule-chain information; Algorithm design and analysis; Association rules; Computer science education; Computer vision; Data mining; Educational technology; Fuzzy systems; Iterative algorithms; Laboratories; Transaction databases; Association rule; Frequent Path Discovery; Incremental Mining; Rule-chain;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Systems and Knowledge Discovery, 2009. FSKD '09. Sixth International Conference on
Conference_Location
Tianjin
Print_ISBN
978-0-7695-3735-1
Type
conf
DOI
10.1109/FSKD.2009.587
Filename
5358679
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