Article: Design and optimisation of museum cultural and creative products based on cultural big data analysis Journal: International Journal of Information and Communication Technology (IJICT) 2026 Vol.27 No.35 pp.1 - 20 Abstract: Museum cultural and creative products often fail to meet audience expectations, leading to low appeal and homogeneity. This study employs a data-driven approach, using NLP and machine learning to analyse 680,000 visitor comments from a provincial museum. Findings show 42% of visitors prefer 'novel, culturally rich' products, yet satisfaction with existing items is low (3.7/5). Data analysis identified the 'bronze ware gluttonous pattern' and 'ancient book calligraphy' as the most valued cultural symbols. Using K-means clustering and A/B testing, new product prototypes were developed. Market tests with 1,000 participants showed a 32% rise in preference, a 26% increase in payment willingness, and a cultural perception score of 4.3. This method effectively enhances product cultural depth and market appeal, offering a viable path for revitalising traditional culture. Inderscience Publishers - linking academia, business and industry through research

Title: Design and optimisation of museum cultural and creative products based on cultural big data analysis

Authors: Bin Jiao

Addresses: Zhengzhou Meiju Industrial Design Co., Ltd., Zhengzhou, 450000, China; School of Innovation and Design, City University of Macau, Macau, 999078, China; School of Art Design, Zhengzhou University of Aeronautics, Zhengzhou, 450000, China

Abstract: Museum cultural and creative products often fail to meet audience expectations, leading to low appeal and homogeneity. This study employs a data-driven approach, using NLP and machine learning to analyse 680,000 visitor comments from a provincial museum. Findings show 42% of visitors prefer 'novel, culturally rich' products, yet satisfaction with existing items is low (3.7/5). Data analysis identified the 'bronze ware gluttonous pattern' and 'ancient book calligraphy' as the most valued cultural symbols. Using K-means clustering and A/B testing, new product prototypes were developed. Market tests with 1,000 participants showed a 32% rise in preference, a 26% increase in payment willingness, and a cultural perception score of 4.3. This method effectively enhances product cultural depth and market appeal, offering a viable path for revitalising traditional culture.

Keywords: cultural big data analysis; museum cultural and creative products; tourist behaviour data; semantic mining; design model construction.

DOI: 10.1504/IJICT.2026.153007

International Journal of Information and Communication Technology, 2026 Vol.27 No.35, pp.1 - 20

Received: 27 Aug 2025
Accepted: 19 Sep 2025
Published online: 17 Apr 2026 *

Title: Design and optimisation of museum cultural and creative products based on cultural big data analysis

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