Domain knowledge-based multilayer association rules mining method and system

Abstract

The invention belongs to the technical field of data mining and specifically discloses a domain knowledge-based multilayer association rules mining method and system. The method comprises the following steps: taking the domain knowledge as basic data and constructing a domain correlation model according to the correlation of the basic data; taking the domain knowledge as the basic data and constructing a structure classification layer according to the basic data; performing clustering storage on the items on the basis of the structure classification layer, thereby generating an item clustering layer and constructing an original transactional database; performing layer classification on the original transactional database and mapping the layer classification into a frequent pattern tree for constructing a frequent pattern tree structure; searching the frequent pattern tree, thereby acquiring a result of a frequent item set. According to the invention, the correctness and completeness of the mining result of the frequent item set are ensured, and the method, compared with the present similar latest mining algorithm, has better executing efficiency and expansibility.

Description

technical field [0001] The invention belongs to the technical field of data mining, and specifically relates to a method and system for mining multi-layer association rules based on domain knowledge. Background technique [0002] In recent years, with the rapid growth of the amount of data, the data mining technology that automatically searches for the special correlation hidden in a large amount of data has emerged as the times require. Data mining technology is the result of long-term research and development of database technology. At first, it was just access and query to the database stored in the computer. Entering the era of massive data, the relevant technologies of data mining are extended to query and traverse data, find potential connections before data, and promote the transmission of information. [0003] Different from the algorithm based on the Aprior idea, since the multi-layer association rule mining problem was proposed, an algorithm based on the FP-Growt...

AI Technical Summary

Problems solved by technology

In general, the disadvantage of the breadth-first algorithm is that it needs to generate a large number of candidate item sets and scan the database multiple times.

But it has application difficulties. When dealing with large and sparse databases, mining processing and recursive operations still require a lot of space.

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