What is it about?

I first normalized the descriptive statistics data, and then constructed a correlation degree calculation method between frequent itemset through the relational structure of the database. Finally, the data mining of key content is carried out by generating significant association rules, and the results of statistical tests prove that the model has strong analysis ability of association degree.

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Why is it important?

With the development of the ice and snow sports market,the data sources of our model can be updated.Product recommendations,etc.,help companies better understand market and customer needs,and improve business efficiency and profitability.In the financial field,it can be used for credit risk assessment,optimization of investment portfolios,and fraud testing to help financial institutions improve risk control capabilities and yields.In terms of municipal planning,it can be used for policy formulation,public safety,urban planning,etc.,helping the government to better understand the needs of people's livelihood and social changes,and improve the scientificity and efficiency of government decision-making.Therefore,this model has a wide range of application prospects.

Perspectives

The innovation of this article lies in: Application innovation: Introduce data mining ideas into the analysis of the ice and snow sports market, which can analyze a large number of association rules and provide guidance suggestions in real-time. Mining multidimensional association rules: Traditional market analysis often only focuses on a few factors, while data mining based on the Apriori algorithm can mine association rules between multiple factors, further revealing potential factors in market development. By analyzing relevant data on various ice and snow movements, some unexpected potential associations can be discovered. Prediction market trend and demand: through mining and analyzing historical data, Apriori algorithm can reveal market development trend and demand changes. Based on past data, we can discover some patterns and patterns to predict future market demand, and formulate corresponding market strategies and decisions based on this, in order to seize market opportunities in advance. Personalized recommendation and customized services: Data mining based on Apriori algorithm can identify common preferences and purchasing patterns among consumers, providing personalized recommendations and customized services for market participants. By analyzing consumers' purchasing history and preferences, we can provide them with products and services that better meet their needs, improve customer satisfaction, and promote market development.

Shangqin Zhou
Wuhan University of Technology

Read the Original

This page is a summary of: Market Analysis System Based on Apriori Algorithm, March 2023, ACM (Association for Computing Machinery),
DOI: 10.1145/3594409.3594428.
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