Dynamic mining of multimedia marketing information for products under the background of data driven

In order to solve the problems of low mining coverage and low product conversion rate in traditional marketing information dynamic mining methods, a new dynamic mining method of multimedia marketing information for products under the background of data driven is proposed. Using web crawler technology to crawl multimedia marketing information data of products, and extracting data features through sliding clustering. By using fuzzy clustering algorithm to perform fuzzy clustering on data features, a clustering dataset item set is constructed and merged into an item set to assign weights. Combined with association rules, dynamic mining of multimedia marketing information for products is achieved. Experimental results have shown that the mining coverage rate of this method is 91~97%, and the product conversion rate is 19.1% when the data volume is 8000. The mining coverage rate and product conversion rate are both at a high level, and the mining effect is good.

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Publication Details

Journal
International Journal of Networking and Virtual Organisations
Published
2025-01-01
DOI
https://doi.org/10.1504/ijnvo.2025.145377
Primary Topic
E-commerce and Technology Innovations
Type
article
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article

Dynamic mining of multimedia marketing information for products under the background of data driven

Yingjun Liu, Kuineng Chen
International Journal of Networking and Virtual Organisations
E-commerce and Technology Innovations
article

Dynamic mining of multimedia marketing information for products under the background of data driven

Yingjun Liu, Kuineng Chen
article en

Abstract

In order to solve the problems of low mining coverage and low product conversion rate in traditional marketing information dynamic mining methods, a new dynamic mining method of multimedia marketing information for products under the background of data driven is proposed. Using web crawler technology to crawl multimedia marketing information data of products, and extracting data features through sliding clustering. By using fuzzy clustering algorithm to perform fuzzy clustering on data features, a clustering dataset item set is constructed and merged into an item set to assign weights. Combined with association rules, dynamic mining of multimedia marketing information for products is achieved. Experimental results have shown that the mining coverage rate of this method is 91~97%, and the product conversion rate is 19.1% when the data volume is 8000. The mining coverage rate and product conversion rate are both at a high level, and the mining effect is good.

International Journal of Networking and Virtual OrganisationsVol. 32(1/2/3/4)
Hunan Vocational Institute of Technology (CN), Loudi Central Hospital (CN)
Decent work and economic growth
Openalex Percentile: Top 90%
E-commerce and Technology Innovations
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Dynamic mining of multimedia marketing information for products under the background of data driven — Yingjun Liu, Kuineng Chen · International Journal of Networking and Virtual Organisations (2025) | TGRS Research Map | TGRS