Communication alarm frequent itemset mining engine and redundancy processing method

Abstract

The invention provides a communication alarm frequent itemset mining engine and a redundancy processing method, particularly architecture and implementation of an engine for communication alarm frequent itemset mining and processing of redundancy thereof. The engine can be used for processing massive alarm information and is independent of the topological structure of the communication network. The invention can be used for efficiently mining out frequent itemsets in an alarm, and processing the redundancy of the mining result, thereby satisfying the demand of practical application. The engine is composed of an alarm data acquiring and preprocessing part, a parameter setting and alarm type converting part, a frequent mode growth improved algorithm part, a mining result redundancy processing part and a final result explaining and displaying part. The alarm frequent itemset mining and redundancy processing engine based on the invention can implement alarm association of the communication network without participation of experts and operational maintenance personnel, and can multiply the processing efficiency at lower operating cost; and thus, the alarm frequent itemset mining and redundancy processing engine is especially suitable for association rule analysis of the communication network, and has wide application prospects and high practical value.

Description

technical field [0001] The invention relates to the field of mobile Internet alarm monitoring, in particular to the field of acquiring alarm frequent item sets based on data mining technology, and in particular to a communication alarm frequent item set mining engine and a redundancy processing method. Background technique [0002] The amount of mobile communication alarms is huge, and when some of them occur, other specific alarms will always occur. These alarms that occur frequently in a period of time are called alarm frequent itemsets. Alarm frequent itemsets imply the main information of alarm association, which is an important basis for our analysis of alarm association. The frequent itemset mining algorithm in data mining can mine the frequent itemsets contained in a large number of alarms from the alarm database, and the frequent pattern growth algorithm can store the alarm information in a frequent pattern tree, by traversing the frequent The pattern tree generates...

AI Technical Summary

Problems solved by technology

The frequent pattern growth algorithm will generate a large number of conditional pattern bases and conditional pattern trees, which makes the efficiency of the algorithm very low, and the obtained frequent itemsets are mostly redundant compared with the actual engineering application, which makes the post-processing work Huge volume, low efficiency

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