An Efficient Method for Mining Informative Association Rules in Knowledge Extraction

Bemarisika, Parfait; Thewis, André

doi:10.1007/978-3-030-57321-8_13

Cited by 3 publications

(2 citation statements)

References 11 publications

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“…Multiple support degrees are also applied to PNARs mining to improve the interesting rules mining efciency in reference [36]. Based on the previous works, Bemarisika and Totohasina [37] proposed a two-level confdence threshold-setting method for positive and negative association rules mining to limit the number of frequent and infrequent items. Also, four confdences are introduced to solve the problem that sole confdence usually results in plenty of useless rules in reference [38].…”

Section: Pnars Mining Techniquesmentioning

confidence: 99%

An Optimized Association Rules Mining Framework for Chinese Social Insurance Fund Data Auditing

Xiuguo,

Shengyong

2023

International Journal of Intelligent Systems

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Association rules mining with the Chinese social insurance fund dataset can effectively discover different kinds of errors, irregularities, and illegal acts by providing auditors with relationships among the items and therefore improve auditing quality and efficiency. However, traditional positive and negative association rules (PNARs) mining algorithms inevitably produce too many meaningless or contradictory rules when these two types of rules are mined simultaneously, which brings a huge challenge to auditors retrieving decision information. Aimed to reduce the quantity of low-reliability PNARs without missing interesting rules, this paper first proposes an improved PNARs mining algorithm with minimum correlation and triple confidence threshold to control the mined rules number by narrowing the range of confidence settings. Then, a novel pruning algorithm based on the inclusion relation of the rule’s antecedent and consequent is given to remove those redundant rules. After that, the proposed optimized PNARs mining approach is applied to the Chinese social insurance fund dataset starting with audit features influence factors mining using the Hash table. The experimental results with different datasets show that the proposed framework not only can ensure effective and interesting rules extraction but also has better performance than traditional approaches in both accuracy and efficiency, reducing the number of redundant PNARs by over 70.1% with experimental datasets and average 78.5% with auditing data mining, respectively.

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Section: Pnars Mining Techniquesmentioning

confidence: 99%

An Optimized Association Rules Mining Framework for Chinese Social Insurance Fund Data Auditing

Xiuguo,

Shengyong

2023

International Journal of Intelligent Systems

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“…Very often, the response time of mining rules is not always better when the database is dense. For this, we adopt a pruning reduce-rules-space procedure [20,21]. The challenge of this procedure is to reduce the number of rules without loss of information.…”

Section: Generating Valid Association Rulesmentioning

confidence: 99%

CONCISE: An Algorithm for Mining Positive and Negative Non-Redundant Association Rules

Bemarisika¹,

Thewis²

2021

SCRS Conference Proceedings on Intelligent Systems

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One challenge problem in association rules mining is the huge size of the extracted rule set many of which are uninteresting and redundant. In this paper, we propose an efficient algorithm CONCISE for generating all non-redundant positive and negative association rules. We first introduce an algorithm CMG (Closed, Maximal and Generators) for mining all frequent closed, maximal and their generators itemsets from large transaction databases. We then define four new bases representing non-redundant association rules from these frequent itemsets. We prove that these bases significantly reduce the number of extracted rules. We show the efficiency of our algorithm by computational experiments compared with existing algorithms.

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Frame Synchronization Method Based on Association Rules for CNAV-2 Messages

Qian

2023

Chinese J. Elect.

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The GPS system is a navigation satellite system with high precision, all-weather service, and global coverage, whose main purpose is to provide real-time and continuous global navigation services for the US military, and whose signal interference in wartime is a heavy blow to the US military. Its existing interference measures are classified into two types: blanket jamming and deception jamming, with the latter having better interference effects due to its imperceptibility. Frame synchronization, as the foundation of deception jamming, is a focus of current research on navigation countermeasures. This paper discusses the frame synchronization of CNAV-2 messages in GPS L1C signals and proposes a frame synchronization algorithm based on association rules. It analyzes the structural characteristics of CNAV-1 message data, reveals the hidden mapping relationships in the BCH code sequence of the first sub-frame by applying association rules, and achieves a blind synchronization of navigation messages by counting the types of mapping relationships and calculating the confidence levels. The simulation test results show that the proposed algorithm displays high error resilience and correct recognition rates and demonstrates certain values in engineering applications.

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An Efficient Method for Mining Informative Association Rules in Knowledge Extraction

Cited by 3 publications

References 11 publications

An Optimized Association Rules Mining Framework for Chinese Social Insurance Fund Data Auditing

An Optimized Association Rules Mining Framework for Chinese Social Insurance Fund Data Auditing

CONCISE: An Algorithm for Mining Positive and Negative Non-Redundant Association Rules

Frame Synchronization Method Based on Association Rules for CNAV-2 Messages

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