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Synthesis excavation method of related rule and metarule

A technology of rules and itemsets, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve the problems of non-periodic association rule change trend analysis and other association rules, etc., to reduce overhead, high efficiency effect

Inactive Publication Date: 2007-09-26
JIANGSU UNIV OF TECH
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Problems solved by technology

[0005] Banu Ozden et al. conducted research on the mining of periodic association rules in "Cyclic Association Rules Mining" (B.Ozden, S.Ramaswamy, and A.Silberschatz.Cyclic Association Rules.In Proc.of the 14th Int.Conf.on Data Engineering, Orlando, Florida, February 1998), the related algorithm proposed in the study can only analyze the changing trend of association rules with periodicity, but cannot analyze the changing trend of aperiodic association rules and some other association rules, such as those that occur steadily

Method used

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  • Synthesis excavation method of related rule and metarule
  • Synthesis excavation method of related rule and metarule
  • Synthesis excavation method of related rule and metarule

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Embodiment Construction

[0025] The steps of the present invention are as follows:

[0026] (1) Divide the time series database into several parts according to time segments;

[0027] (2) Scan each part in turn, and form frequent 1-itemsets in each part;

[0028] (3) Scan each part separately again to form a frequent 1-itemset superstructure;

[0029] (4) Form a fully constructed superstructure by recursive decomposition;

[0030] (5) Mining superstructure to form association rules and meta-rules.

[0031] In the next step, the meta-rules are input to the BP neural network for classification, and the meta-rules of classification are obtained.

[0032] The following is the specific construction process:

[0033] (1) Construction of the superstructure

[0034] (a) Construction of the superstructure header table

[0035] The superstructure header table contains two fields: the item length field and the pointer field. The pointer in the pointer field points to the corresponding hash chain structure...

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Abstract

This invention relates to one correlation rules and its element rules integral digging method, which comprises the following steps: a, diving the time sequence database on time into several parts; b, orderly scanning each part to form frequency item set; c, then scanning each part to form frequency item super structure; d, adopting recursive method to form super structure; e, digging super structure to form correlation rules and element rules. This invention only needs scan data twice to get whole strong relative rule set, each time section strong relation rules set and element set.

Description

technical field [0001] The invention relates to computer data processing, and is a comprehensive mining method for association rules and meta-rules Background technique [0002] Data mining is an important branch in the field of artificial intelligence, and the mining of association rules is an important task for many data mining problems. However, the existing single algorithms cannot simultaneously meet the requirements of mining association rules, meta-rules, and association rules. If various algorithms are combined for mining, the mining efficiency will be greatly reduced. For the mining of meta-rules, the existing algorithms can only be adapted to the same data domain for mining. [0003] At present, the more influential frequent pattern mining method in the world is the Apriori algorithm (R.Agrawal and R.Srikant.Fast algorithms for mining association rules.In VLDB'94, pages 487-499) and its related improved algorithms, such as DCP (S. Orlando, P. Palmerini and R. Pere...

Claims

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Application Information

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IPC IPC(8): G06F17/30
Inventor 叶飞跃
Owner JIANGSU UNIV OF TECH
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