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

Authors: Yingjun Liu; Kuineng Chen

Addresses: Department of Business, Loudi Vocational and Technical College, Loudi, 417000, China ' Department of Intelligent Manufacturing, Hunan Vocational Institute of Technology, Xiangtan, 411100, China

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.

Keywords: data driven; multimedia marketing information; dynamic mining; fuzzy clustering; association rules.

DOI: 10.1504/IJNVO.2025.145377

International Journal of Networking and Virtual Organisations, 2025 Vol.32 No.1/2/3/4, pp.119 - 134

Received: 03 Jun 2024
Accepted: 22 Sep 2024
Published online: 31 Mar 2025 *

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