Data Mining Techniques and Strategies in Digital Asset Management in Cultural Museums

Abstract

The development trend of digital assets characteristic of public cultural service units involves the rational and standardized management of existing and future-generated digital resources. The study examines the significance of data mining technology in the digital asset management system of cultural museums. For the information retrieval service involved in the system, an improved decision tree algorithm based on mutual information is proposed as the data mining kernel by improving the ID3 algorithm to achieve fast and effective information retrieval of multi-source data. On different domain sets, the average retrieval speed of the improved decision tree algorithm is 6.87 ms, which is better than the Random Forest algorithm and Bagging algorithm, and it is able to accurately retrieve the data location of digital assets. This paper proposes to improve the management of digital assets in cultural museums from three aspects: innovating the institutional mechanism, standardizing the account management of digital assets, and establishing an intelligent promotion platform for digital assets.