A Method to Optimize Apriori Algorithm for Frequent Items Mining

Zhang, Ke; Liu, Jianhuan; Chai, Yi; Zhou, Jiayi; Li, Yi

doi:10.1109/iscid.2014.233

Cited by 8 publications

(3 citation statements)

References 9 publications

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“…To achieve this objective, we leverage an improved Apriori algorithm to mine association rules between these factors and their combined effects on air pollution concentration. Unlike the traditional Apriori algorithm, which requires repetitive database scans to generate candidates, consuming substantial time and memory (Zhang et al., 2014), our study introduces lift as an evaluation metric. This significantly reduces the algorithm's runtime and allows for more effective rule filtering, yielding more persuasive rules, and enhance the applicability and contribution to environmental protection strategies.…”

Section: Discussionmentioning

confidence: 99%

Association rule mining of air quality through an improved Apriori algorithm: A case study in 244 Chinese cities

Shen,

Tian,

et al. 2024

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Predicting air pollution is complex due to intertwined factors among local climate, built environment, and development stages. This study leverages K‐means clustering and an improved Apriori algorithm to investigate the combined effects of local meteorological, morphological, and socioeconomic factors on air quality in 244 prefectural‐level Chinese cities. Results reveal that the secondary industry in GDP and saturation vapor pressure strongly relate to air quality. Severe air pollution occurs when urban development is coupled with reduced green areas and high temperatures, confirming that a single factor cannot predict air quality well. For example, we find that combining low population, low regional GDP, high maximum temperatures, and longer roads worsens air quality in small urban built‐up areas. Additionally, temperature and altitude differences associate with highway passenger volume, regional GDP, and population differently. Given our rules mining methods have broader applications in diversified urban environments, this study provides new insights for improving air quality and local Sustainable Development Goals.

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Section: Discussionmentioning

confidence: 99%

Association rule mining of air quality through an improved Apriori algorithm: A case study in 244 Chinese cities

Shen,

Tian,

et al. 2024

Transactions in GIS

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“…In 2013, Zhang et al [5] proposed the OApriori algorithm, which is based on the transaction reduction technique and database mapping technique. In this method, they have optimized a mapping method of the database and the connection setup.…”

Section: Database Mappingmentioning

confidence: 99%

“…Under the best-case scenario, L k−1 can meet the requirements with just one scan. But in the worst-case scenario, the requirements will not be met until scanning L k−1 , k times [5]. This research analyses the basic ideas and shortcomings of Apriori algorithm and compare several different styles of the major improvement strategies.…”

Section: Introductionmentioning

confidence: 99%

A Novel Approach to Enhance the Efficiency of Apriori Algorithm

Herath,

Wijenayake

2024

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Data mining is the process of obtaining valuable or significant information from a large-scale database. One significantarea of research in the field of data mining is association rules mining. Apriori algorithm is one of the classical algorithmsin the association rule mining field. This research analyses the basic ideas and shortcomings of the Apriori algorithm andcompares several different styles of its major improvement strategies. Then it suggests an improved version of the Apriorialgorithm that utilizes a dataset summarization method, an optimized database mapping technique, an intersection operation,and a joined optimization strategy. These enhancements aim to address the low performance and efficiency by reducing thegeneration of candidate itemsets and minimizing the execution time. This addresses the issues of generating numerous candidate itemsets and repeatedly scanning the transaction database. After implementing the optimized algorithm, to verify its effectiveness, it has been applied to a groceries dataset, which is for market basket analysis. The improved Apriori algorithm demonstrated significant enhancements over the original algorithm in terms of reduced candidate itemsets and running time, leading to improved algorithm efficiency.

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An Optimized Apriori Algorithm Applied to Student Achievement Data

Zhao

Wang

2021

Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery

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A Method to Optimize Apriori Algorithm for Frequent Items Mining

Cited by 8 publications

References 9 publications

Association rule mining of air quality through an improved Apriori algorithm: A case study in 244 Chinese cities

Association rule mining of air quality through an improved Apriori algorithm: A case study in 244 Chinese cities

A Novel Approach to Enhance the Efficiency of Apriori Algorithm

An Optimized Apriori Algorithm Applied to Student Achievement Data

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